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modelId
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139
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| last_modified
timestamp[us, tz=UTC]date 2020-02-15 11:33:14
2025-06-26 00:41:36
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int64 0
223M
| likes
int64 0
11.7k
| library_name
stringclasses 496
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timestamp[us, tz=UTC]date 2022-03-02 23:29:04
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aranoo/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-moist_prowling_hawk | aranoo | 2025-06-26T00:17:32 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am moist prowling hawk",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:unsloth/Qwen2.5-0.5B-Instruct",
"base_model:finetune:unsloth/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-26T00:16:36 | Temporary Redirect. Redirecting to /api/resolve-cache/models/aranoo/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-moist_prowling_hawk/583c43953dc52ad1d8fc472f7df3973530e7474f/README.md?%2Faranoo%2FQwen2.5-0.5B-Instruct-Gensyn-Swarm-moist_prowling_hawk%2Fresolve%2Fmain%2FREADME.md=&etag=%22e45482d82ec7a48f013d4fe53db92aca8733efbc%22 |
haedahae/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-unseen_giant_raccoon | haedahae | 2025-06-26T00:11:18 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am unseen giant raccoon",
"unsloth",
"trl",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-1.5B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-05-29T03:45:00 | Temporary Redirect. Redirecting to /api/resolve-cache/models/haedahae/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-unseen_giant_raccoon/f6b6c263bf012d639ce7f731370755a924a32de7/README.md?%2Fhaedahae%2FQwen2.5-1.5B-Instruct-Gensyn-Swarm-unseen_giant_raccoon%2Fresolve%2Fmain%2FREADME.md=&etag=%226ced8d4cf036458c2b904cf9e799116516c509a7%22 |
ArliAI/DS-R1-Distill-70B-ArliAI-RpR-v4-Large | ArliAI | 2025-06-25T23:54:38 | 164 | 7 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"en",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"base_model:finetune:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"license:llama3.3",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-06T15:39:06 | Temporary Redirect. Redirecting to /api/resolve-cache/models/ArliAI/DS-R1-Distill-70B-ArliAI-RpR-v4-Large/f5eb02c877220331679a1ca3acfdd12e74b7304a/README.md?%2FArliAI%2FDS-R1-Distill-70B-ArliAI-RpR-v4-Large%2Fresolve%2Fmain%2FREADME.md=&etag=%2282b53fea3365a6814a960c1661dd7e3acc16bc37%22 |
haedahae/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-hoarse_hairy_lion | haedahae | 2025-06-25T23:14:10 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am hoarse hairy lion",
"unsloth",
"trl",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-1.5B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-06-22T10:12:43 | Temporary Redirect. Redirecting to /api/resolve-cache/models/haedahae/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-hoarse_hairy_lion/d670029c1712607e7c89c27bb1d1bda666aab5fc/README.md?%2Fhaedahae%2FQwen2.5-1.5B-Instruct-Gensyn-Swarm-hoarse_hairy_lion%2Fresolve%2Fmain%2FREADME.md=&etag=%22e5d73eeaab00484646b90c1652c45c06b60acde5%22 |
izzymiller95/caret-1-dpo-relabeled | izzymiller95 | 2025-06-25T22:41:32 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"text-generation-inference",
"unsloth",
"conversational",
"en",
"base_model:izzymiller95/caret-beta-1",
"base_model:finetune:izzymiller95/caret-beta-1",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T12:01:34 | Temporary Redirect. Redirecting to /api/resolve-cache/models/izzymiller95/caret-1-dpo-relabeled/2843072ab07e856df131a5a70427c14b56cf9738/README.md?%2Fizzymiller95%2Fcaret-1-dpo-relabeled%2Fresolve%2Fmain%2FREADME.md=&etag=%222edf58302f0f59c6d6f793e4bb95032cd767a088%22 |
pweidel/pii-bert-redactor | pweidel | 2025-06-25T22:36:35 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"token-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | 2025-06-25T18:07:44 | Temporary Redirect. Redirecting to /api/resolve-cache/models/pweidel/pii-bert-redactor/41351a07112784178ec60216e84955171e046f27/README.md?%2Fpweidel%2Fpii-bert-redactor%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
ramyakeerthyt/outputs30km | ramyakeerthyt | 2025-06-25T22:22:20 | 0 | 0 | peft | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2025-06-24T17:07:41 | Temporary Redirect. Redirecting to /api/resolve-cache/models/ramyakeerthyt/outputs30km/4b47cf23c1df1b8c2554a5ae7f5d48091cacaddc/README.md?%2Framyakeerthyt%2Foutputs30km%2Fresolve%2Fmain%2FREADME.md=&etag=%2204aaa62385bc281cd21322f4d1d4cebe7a43b600%22 |
ArliAI/QwQ-32B-ArliAI-RpR-v4 | ArliAI | 2025-06-25T21:34:52 | 2,805 | 26 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"en",
"base_model:Qwen/QwQ-32B",
"base_model:finetune:Qwen/QwQ-32B",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-05-22T05:19:22 | Temporary Redirect. Redirecting to /api/resolve-cache/models/ArliAI/QwQ-32B-ArliAI-RpR-v4/ad85eec4a5114a37bf974accbdd5afc062759231/README.md?%2FArliAI%2FQwQ-32B-ArliAI-RpR-v4%2Fresolve%2Fmain%2FREADME.md=&etag=%226729bec97512aedb7011e8dbca8b7488e79bc5d6%22 |
tomaarsen/splade-cocondenser-msmarco-kldiv-minilm-temp-4-4-threshold | tomaarsen | 2025-06-25T21:21:00 | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sparse-encoder",
"sparse",
"splade",
"generated_from_trainer",
"dataset_size:99000",
"loss:SpladeLoss",
"loss:SparseDistillKLDivLoss",
"loss:FlopsLoss",
"feature-extraction",
"en",
"arxiv:1908.10084",
"arxiv:2205.04733",
"arxiv:2010.11386",
"arxiv:2004.05665",
"base_model:Luyu/co-condenser-marco",
"base_model:finetune:Luyu/co-condenser-marco",
"license:apache-2.0",
"model-index",
"co2_eq_emissions",
"autotrain_compatible",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2025-06-25T21:20:50 | Temporary Redirect. Redirecting to /api/resolve-cache/models/tomaarsen/splade-cocondenser-msmarco-kldiv-minilm-temp-4-4-threshold/a3226e8054fe2a39fcd5273e94a0654ee3c7c1eb/README.md?%2Ftomaarsen%2Fsplade-cocondenser-msmarco-kldiv-minilm-temp-4-4-threshold%2Fresolve%2Fmain%2FREADME.md=&etag=%229456fea48d5aceb6c2562ee9f0ea7015fac6664e%22 |
mradermacher/ShotVL-7B-GGUF | mradermacher | 2025-06-25T20:59:29 | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Vchitect/ShotVL-7B",
"base_model:quantized:Vchitect/ShotVL-7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-06-25T16:56:33 | Temporary Redirect. Redirecting to /api/resolve-cache/models/mradermacher/ShotVL-7B-GGUF/6702fa2b7583a99d84c54f7edaa92a81e87bfe26/README.md?%2Fmradermacher%2FShotVL-7B-GGUF%2Fresolve%2Fmain%2FREADME.md=&etag=%225afb46852a4780db012fa6ec557fbfe0461f07c4%22 |
hasancanonder/Llama-3.2-1B-Turkish-Instruct-Q4_K_M-GGUF | hasancanonder | 2025-06-25T20:51:38 | 0 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"llama",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:hasancanonder/Llama-3.2-1B-Turkish-Instruct",
"base_model:quantized:hasancanonder/Llama-3.2-1B-Turkish-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-06-25T20:51:32 | Temporary Redirect. Redirecting to /api/resolve-cache/models/hasancanonder/Llama-3.2-1B-Turkish-Instruct-Q4_K_M-GGUF/858bb5c01a69e23edaa5e3dd456404004caaba7f/README.md?%2Fhasancanonder%2FLlama-3.2-1B-Turkish-Instruct-Q4_K_M-GGUF%2Fresolve%2Fmain%2FREADME.md=&etag=%225b2dcd07513e8b09e07920fac4166337365236b6%22 |
ezzzeee/my_smolvla | ezzzeee | 2025-06-25T20:21:29 | 38 | 2 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-06-15T17:50:36 | Temporary Redirect. Redirecting to /api/resolve-cache/models/ezzzeee/my_smolvla/8b6608062ccdfc5ff52e14e5a8bb075c70b4c881/README.md?%2Fezzzeee%2Fmy_smolvla%2Fresolve%2Fmain%2FREADME.md=&etag=%22bcc802cfe87983596ac1caa791176e96ba0860e8%22 |
New-videos-Bts-Wiki-Com-viral-Clips/FULL.VIDEO.Bts.Wiki.Com.Viral.Video.Tutorial.Official | New-videos-Bts-Wiki-Com-viral-Clips | 2025-06-25T20:20:46 | 0 | 0 | null | [
"region:us"
] | null | 2025-06-25T20:20:37 | Temporary Redirect. Redirecting to /api/resolve-cache/models/New-videos-Bts-Wiki-Com-viral-Clips/FULL.VIDEO.Bts.Wiki.Com.Viral.Video.Tutorial.Official/c9eec96f7714cfd50fd54adb1553bf102d0ba526/README.md?%2FNew-videos-Bts-Wiki-Com-viral-Clips%2FFULL.VIDEO.Bts.Wiki.Com.Viral.Video.Tutorial.Official%2Fresolve%2Fmain%2FREADME.md=&etag=%225641dca3bc2994433ce5d4611cba82313c5dcf68%22 |
NICOPOI-9/segformer-b5-finetuned-morphpadver1-hgo-coord-v9_mix_resample_40epochs | NICOPOI-9 | 2025-06-25T19:43:49 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"segformer",
"vision",
"image-segmentation",
"generated_from_trainer",
"base_model:nvidia/mit-b5",
"base_model:finetune:nvidia/mit-b5",
"license:other",
"endpoints_compatible",
"region:us"
] | image-segmentation | 2025-06-25T07:11:01 | Temporary Redirect. Redirecting to /api/resolve-cache/models/NICOPOI-9/segformer-b5-finetuned-morphpadver1-hgo-coord-v9_mix_resample_40epochs/cbd94bb9c9d1df0b2d8c280e4207d585c9febee1/README.md?%2FNICOPOI-9%2Fsegformer-b5-finetuned-morphpadver1-hgo-coord-v9_mix_resample_40epochs%2Fresolve%2Fmain%2FREADME.md=&etag=%220120234b2d01fd7aa8eea886e9099c8f930a1e44%22 |
Instasteamml/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-deadly_camouflaged_koala | Instasteamml | 2025-06-25T19:38:20 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am deadly camouflaged koala",
"unsloth",
"trl",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-1.5B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-06-23T01:34:52 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Instasteamml/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-deadly_camouflaged_koala/3a061018947ce80086921edfe09bc26e3bff4444/README.md?%2FInstasteamml%2FQwen2.5-1.5B-Instruct-Gensyn-Swarm-deadly_camouflaged_koala%2Fresolve%2Fmain%2FREADME.md=&etag=%22562d7c0e85fb0cddfff102a5080479de9602a282%22 |
bajirut/03d5084e-a638-4c1b-b635-3f04efef07dc | bajirut | 2025-06-25T19:28:15 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"unsloth",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T17:24:33 | Temporary Redirect. Redirecting to /api/resolve-cache/models/bajirut/03d5084e-a638-4c1b-b635-3f04efef07dc/36c3e31361810267dd6998243f49b04a4c19a385/README.md?%2Fbajirut%2F03d5084e-a638-4c1b-b635-3f04efef07dc%2Fresolve%2Fmain%2FREADME.md=&etag=%22b7441640181b06c90effb718230b043e35476812%22 |
phospho-app/kaykhi-gr00t-pickup_first_test6-3cgcu | phospho-app | 2025-06-25T19:13:57 | 0 | 0 | null | [
"safetensors",
"gr00t_n1",
"phosphobot",
"gr00t",
"region:us"
] | null | 2025-06-25T16:21:10 | Temporary Redirect. Redirecting to /api/resolve-cache/models/phospho-app/kaykhi-gr00t-pickup_first_test6-3cgcu/d6e35ad681f3a75985603be3d98214781d0c20bf/README.md?%2Fphospho-app%2Fkaykhi-gr00t-pickup_first_test6-3cgcu%2Fresolve%2Fmain%2FREADME.md=&etag=%22e7c462cf46bd99e863971dbf8e2eedeadf9f4ced%22 |
p2g3ads4/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-camouflaged_tame_alpaca | p2g3ads4 | 2025-06-25T19:13:54 | 51 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am camouflaged tame alpaca",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:unsloth/Qwen2.5-0.5B-Instruct",
"base_model:finetune:unsloth/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-20T20:19:45 | Temporary Redirect. Redirecting to /api/resolve-cache/models/p2g3ads4/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-camouflaged_tame_alpaca/863af0e7f969d7fe99b956ef91d1e72b5122be30/README.md?%2Fp2g3ads4%2FQwen2.5-0.5B-Instruct-Gensyn-Swarm-camouflaged_tame_alpaca%2Fresolve%2Fmain%2FREADME.md=&etag=%220771e008c440f6eb3dec836a2de33c37b50596c1%22 |
yuto-urushima/act_so101_test | yuto-urushima | 2025-06-25T18:51:52 | 10 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"license:apache-2.0",
"region:us"
] | robotics | 2025-05-23T00:20:03 | Temporary Redirect. Redirecting to /api/resolve-cache/models/yuto-urushima/act_so101_test/a017295e074506267e77fbefe0e18da3e41266b6/README.md?%2Fyuto-urushima%2Fact_so101_test%2Fresolve%2Fmain%2FREADME.md=&etag=%22548a3cad3d3ca30ff2d320d99c38109e3e711714%22 |
iscsir/finetuning-sentiment-model-3000-samples | iscsir | 2025-06-25T18:14:58 | 10 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2024-12-06T19:17:26 | Temporary Redirect. Redirecting to /api/resolve-cache/models/iscsir/finetuning-sentiment-model-3000-samples/83482d0652194d60561ff75c6311662dbef47b97/README.md?%2Fiscsir%2Ffinetuning-sentiment-model-3000-samples%2Fresolve%2Fmain%2FREADME.md=&etag=%222705803c872ff8ef0aa8eafa12ed8624eb11f09a%22 |
New-virals-Sajal-Malik-viral-video-Clips/FULL.VIDEO.Sajal.Malik.Viral.Video.Tutorial.Official | New-virals-Sajal-Malik-viral-video-Clips | 2025-06-25T18:12:49 | 0 | 0 | null | [
"region:us"
] | null | 2025-06-25T18:12:29 | Temporary Redirect. Redirecting to /api/resolve-cache/models/New-virals-Sajal-Malik-viral-video-Clips/FULL.VIDEO.Sajal.Malik.Viral.Video.Tutorial.Official/863f802e2bd4ca3ce04d52d69c882aebfafa52aa/README.md?%2FNew-virals-Sajal-Malik-viral-video-Clips%2FFULL.VIDEO.Sajal.Malik.Viral.Video.Tutorial.Official%2Fresolve%2Fmain%2FREADME.md=&etag=%2207dc5cfc031d072d725e73c4293cb19b5e9b5e73%22 |
ninczar/hingrynt | ninczar | 2025-06-25T18:08:14 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T17:01:59 | Temporary Redirect. Redirecting to /api/resolve-cache/models/ninczar/hingrynt/05ba2cf548bd1086345ac7290292227bd6e347bc/README.md?%2Fninczar%2Fhingrynt%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
r831/finetuned-distibert-sentiment | r831 | 2025-06-25T18:03:45 | 50 | 1 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"sentiment-analysis",
"huggingface",
"arxiv:1910.01108",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-06-13T09:54:02 | Temporary Redirect. Redirecting to /api/resolve-cache/models/r831/finetuned-distibert-sentiment/7ef59ba95c7ca6accbfffb3ce1a8ad1eb9564188/README.md?%2Fr831%2Ffinetuned-distibert-sentiment%2Fresolve%2Fmain%2FREADME.md=&etag=%22468ea427fc45a2b629cda4e712552b8330cb3f80%22 |
SpaceMarines/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-elusive_colorful_ape | SpaceMarines | 2025-06-25T18:02:27 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am elusive colorful ape",
"unsloth",
"trl",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-1.5B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-06-24T16:33:43 | Temporary Redirect. Redirecting to /api/resolve-cache/models/SpaceMarines/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-elusive_colorful_ape/e4453d00bc781af8c8e8a3a1b5729882647d6634/README.md?%2FSpaceMarines%2FQwen2.5-1.5B-Instruct-Gensyn-Swarm-elusive_colorful_ape%2Fresolve%2Fmain%2FREADME.md=&etag=%22c3280b7832a9a905a65592bfb6ed4183bea55d8c%22 |
amai-gsu/SmolLM2-1.7B-Instruct-Q4_K_M-GGUF | amai-gsu | 2025-06-25T18:00:42 | 0 | 0 | transformers | [
"transformers",
"gguf",
"safetensors",
"onnx",
"transformers.js",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"base_model:HuggingFaceTB/SmolLM2-1.7B-Instruct",
"base_model:quantized:HuggingFaceTB/SmolLM2-1.7B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-06-25T18:00:34 | Temporary Redirect. Redirecting to /api/resolve-cache/models/amai-gsu/SmolLM2-1.7B-Instruct-Q4_K_M-GGUF/faa8b82045ebe6fbd7b55ab34f9d1ee6f1ff8d75/README.md?%2Famai-gsu%2FSmolLM2-1.7B-Instruct-Q4_K_M-GGUF%2Fresolve%2Fmain%2FREADME.md=&etag=%22d0433ff78909108c9566a9d02ca62d54e571016a%22 |
Motocat/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-rabid_vigilant_caterpillar | Motocat | 2025-06-25T17:59:45 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am rabid vigilant caterpillar",
"unsloth",
"trl",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-1.5B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-06-11T03:35:02 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Motocat/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-rabid_vigilant_caterpillar/738cb2a0b40b0cfab1c0810fcff950b106b63874/README.md?%2FMotocat%2FQwen2.5-1.5B-Instruct-Gensyn-Swarm-rabid_vigilant_caterpillar%2Fresolve%2Fmain%2FREADME.md=&etag=%22f91d3130814044e5250e4a93539fe5e530c1f5c8%22 |
New-virals-camilla-araujo-viral-video-Clip/FULL.VIDEO.camilla.araujo.Viral.Video.Tutorial.Official | New-virals-camilla-araujo-viral-video-Clip | 2025-06-25T17:53:16 | 0 | 0 | null | [
"region:us"
] | null | 2025-06-25T17:52:37 | Temporary Redirect. Redirecting to /api/resolve-cache/models/New-virals-camilla-araujo-viral-video-Clip/FULL.VIDEO.camilla.araujo.Viral.Video.Tutorial.Official/49a9ec22e61d0d3f8dbf10c18caa0c8f2d56eb4b/README.md?%2FNew-virals-camilla-araujo-viral-video-Clip%2FFULL.VIDEO.camilla.araujo.Viral.Video.Tutorial.Official%2Fresolve%2Fmain%2FREADME.md=&etag=%2207dc5cfc031d072d725e73c4293cb19b5e9b5e73%22 |
balandinnikita/TableSlateSkivaro | balandinnikita | 2025-06-25T17:28:15 | 0 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-06-25T17:07:28 | Temporary Redirect. Redirecting to /api/resolve-cache/models/balandinnikita/TableSlateSkivaro/46007ff9821579c7890254e33d7e17af80bd2c44/README.md?%2Fbalandinnikita%2FTableSlateSkivaro%2Fresolve%2Fmain%2FREADME.md=&etag=%22d86b15b9f4d6a549cd71b47560727451ccc0f7e2%22 |
qualcomm/PPE-Detection | qualcomm | 2025-06-25T17:28:10 | 144 | 0 | pytorch | [
"pytorch",
"tflite",
"onnx",
"real_time",
"android",
"object-detection",
"license:other",
"region:us"
] | object-detection | 2024-10-21T23:27:00 | Temporary Redirect. Redirecting to /api/resolve-cache/models/qualcomm/PPE-Detection/062f8e1b69a91bb2ec0066ea4a40c7a0711430f2/README.md?%2Fqualcomm%2FPPE-Detection%2Fresolve%2Fmain%2FREADME.md=&etag=%220157e0a917ded3f3dda42e8654fc27bc9326d96b%22 |
Timia123/tdpo_iter3_jun24 | Timia123 | 2025-06-25T17:00:13 | 0 | 0 | null | [
"safetensors",
"llama",
"license:apache-2.0",
"region:us"
] | null | 2025-06-25T16:56:37 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Timia123/tdpo_iter3_jun24/3bc4319ecd97becd3b17a2a148a69a197cab4e3e/README.md?%2FTimia123%2Ftdpo_iter3_jun24%2Fresolve%2Fmain%2FREADME.md=&etag=%227b95401dc46245ac339fc25059d4a56d90b4cde5%22 |
marcel-gohsen/qpt2-medium-aql-mix-inst-aol-query-log | marcel-gohsen | 2025-06-25T16:57:37 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T16:57:11 | Temporary Redirect. Redirecting to /api/resolve-cache/models/marcel-gohsen/qpt2-medium-aql-mix-inst-aol-query-log/8a372f0d1b4189fddfa6d31df7a1a98532572146/README.md?%2Fmarcel-gohsen%2Fqpt2-medium-aql-mix-inst-aol-query-log%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
link-pakcricketinfo-sapna-shah-Viral-video/VIDEO.Pakcricketinfo.Sapna.Shah.Viral.Video.Official.Tutorial | link-pakcricketinfo-sapna-shah-Viral-video | 2025-06-25T16:44:23 | 0 | 0 | null | [
"region:us"
] | null | 2025-06-25T16:43:06 | Temporary Redirect. Redirecting to /api/resolve-cache/models/link-pakcricketinfo-sapna-shah-Viral-video/VIDEO.Pakcricketinfo.Sapna.Shah.Viral.Video.Official.Tutorial/d1d72cf973e8c2c388876b68761103a832fc0671/README.md?%2Flink-pakcricketinfo-sapna-shah-Viral-video%2FVIDEO.Pakcricketinfo.Sapna.Shah.Viral.Video.Official.Tutorial%2Fresolve%2Fmain%2FREADME.md=&etag=%225b963c16fa50cc0ca401f4a16b8a8a442b89589b%22 |
vuitton/master2 | vuitton | 2025-06-25T16:39:17 | 0 | 0 | null | [
"safetensors",
"any-to-any",
"omega",
"omegalabs",
"bittensor",
"agi",
"license:mit",
"region:us"
] | any-to-any | 2025-06-25T16:32:43 | Temporary Redirect. Redirecting to /api/resolve-cache/models/vuitton/master2/76aee8e5587a33be8cfdd9b8cc5e4c27ec8bb1a6/README.md?%2Fvuitton%2Fmaster2%2Fresolve%2Fmain%2FREADME.md=&etag=%2213a6bd2875d0f87525e8d8c5b1cf31c9ccc08b34%22 |
AliMurtaza-096/finetuned-smollm2-1.7B-instruct | AliMurtaza-096 | 2025-06-25T16:25:13 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T16:23:58 | Temporary Redirect. Redirecting to /api/resolve-cache/models/AliMurtaza-096/finetuned-smollm2-1.7B-instruct/6a7e6058322979d713ba7c4b5de595f22f7ddb15/README.md?%2FAliMurtaza-096%2Ffinetuned-smollm2-1.7B-instruct%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
vuitton/fish1 | vuitton | 2025-06-25T16:22:26 | 0 | 0 | null | [
"safetensors",
"any-to-any",
"omega",
"omegalabs",
"bittensor",
"agi",
"license:mit",
"region:us"
] | any-to-any | 2025-06-25T15:58:46 | Temporary Redirect. Redirecting to /api/resolve-cache/models/vuitton/fish1/0bc9cbc7c1819c7078022b96ee7535b51c7bfd0e/README.md?%2Fvuitton%2Ffish1%2Fresolve%2Fmain%2FREADME.md=&etag=%2213a6bd2875d0f87525e8d8c5b1cf31c9ccc08b34%22 |
Edcastro/tinyllama-edcastr_Guardrail-v1 | Edcastro | 2025-06-25T16:18:23 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T16:16:55 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Edcastro/tinyllama-edcastr_Guardrail-v1/ee3763d98b1ca6341d25e387a7dff995e7cfa55d/README.md?%2FEdcastro%2Ftinyllama-edcastr_Guardrail-v1%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
gokulsrinivasagan/codebert_base_code_uml_c | gokulsrinivasagan | 2025-06-25T16:17:15 | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"fill-mask",
"generated_from_trainer",
"dataset:devgpt-aimotion/the-stack-v2_PlantUML_filtered",
"base_model:microsoft/codebert-base-mlm",
"base_model:finetune:microsoft/codebert-base-mlm",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | fill-mask | 2025-06-25T13:21:09 | Temporary Redirect. Redirecting to /api/resolve-cache/models/gokulsrinivasagan/codebert_base_code_uml_c/a913ed8f39a0e7123abca44b9126d9cb5b2a43bb/README.md?%2Fgokulsrinivasagan%2Fcodebert_base_code_uml_c%2Fresolve%2Fmain%2FREADME.md=&etag=%22f87e5131fbbf1dab856ec76042ef2a9ec2e52379%22 |
pakcricketinfo-sapna-shah-videos/fUll.wATCH.pakcricketinfo.sapna.shah.viral.video.original.telegram.link | pakcricketinfo-sapna-shah-videos | 2025-06-25T16:15:09 | 0 | 0 | null | [
"region:us"
] | null | 2025-06-25T16:13:03 | Temporary Redirect. Redirecting to /api/resolve-cache/models/pakcricketinfo-sapna-shah-videos/fUll.wATCH.pakcricketinfo.sapna.shah.viral.video.original.telegram.link/cb067d69b2253020364190d2a71bfdc25e876523/README.md?%2Fpakcricketinfo-sapna-shah-videos%2FfUll.wATCH.pakcricketinfo.sapna.shah.viral.video.original.telegram.link%2Fresolve%2Fmain%2FREADME.md=&etag=%22099ff35964e50c5b04eadfc1cb895444fbe6a73f%22 |
Marcjoni/KiloNovaSynth-12B | Marcjoni | 2025-06-25T15:57:29 | 0 | 1 | null | [
"safetensors",
"mistral",
"merge",
"mergekit",
"lazymergekit",
"DreadPoor/Irix-12B-Model_Stock",
"yamatazen/LorablatedStock-12B",
"yamatazen/EtherealAurora-12B-v2",
"base_model:DreadPoor/Irix-12B-Model_Stock",
"base_model:merge:DreadPoor/Irix-12B-Model_Stock",
"base_model:yamatazen/EtherealAurora-12B-v2",
"base_model:merge:yamatazen/EtherealAurora-12B-v2",
"base_model:yamatazen/LorablatedStock-12B",
"base_model:merge:yamatazen/LorablatedStock-12B",
"region:us"
] | null | 2025-06-25T15:44:05 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Marcjoni/KiloNovaSynth-12B/e8e1486329236dfae5d9fdb6128c7aed6aa4c965/README.md?%2FMarcjoni%2FKiloNovaSynth-12B%2Fresolve%2Fmain%2FREADME.md=&etag=%22b923f936082f8c5c6254b2142ae2887bcb603507%22 |
ertghiu256/Gemma-3-Qwentified | ertghiu256 | 2025-06-25T15:42:15 | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2025-06-25T15:42:15 | Temporary Redirect. Redirecting to /api/resolve-cache/models/ertghiu256/Gemma-3-Qwentified/256534f6b21049981dc6e1514c1fa85b9c9d0660/README.md?%2Fertghiu256%2FGemma-3-Qwentified%2Fresolve%2Fmain%2FREADME.md=&etag=%227b95401dc46245ac339fc25059d4a56d90b4cde5%22 |
cyberdelia/controlnet_files | cyberdelia | 2025-06-25T15:23:17 | 0 | 1 | diffusers | [
"diffusers",
"stable-diffusion",
"sd-1.5",
"text-to-image",
"photorealistic",
"cyberrealistic",
"image-generation",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2025-05-25T09:19:48 | Temporary Redirect. Redirecting to /api/resolve-cache/models/cyberdelia/controlnet_files/0818ca2f40a560b4cb6fe67db8c145b56ed396b0/README.md?%2Fcyberdelia%2Fcontrolnet_files%2Fresolve%2Fmain%2FREADME.md=&etag=%2266afa107a1fdd6023e73c4b80e15beaedc6df3ea%22 |
jcrzd/unsloth_finetune | jcrzd | 2025-06-25T15:16:51 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mllama",
"image-text-to-text",
"text-generation-inference",
"unsloth",
"conversational",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-06-25T15:16:34 | Temporary Redirect. Redirecting to /api/resolve-cache/models/jcrzd/unsloth_finetune/cf684a228ff8a9eca93e5ce13be31cd23a243aca/README.md?%2Fjcrzd%2Funsloth_finetune%2Fresolve%2Fmain%2FREADME.md=&etag=%220b7df1c7ee03c7d4fbaa888fbe86eed54eba1fae%22 |
phospho-app/GarrieD-ACT-Red_Ball_V1_0625 | phospho-app | 2025-06-25T15:13:39 | 0 | 0 | null | [
"safetensors",
"phosphobot",
"act",
"region:us"
] | null | 2025-06-25T13:46:01 | Temporary Redirect. Redirecting to /api/resolve-cache/models/phospho-app/GarrieD-ACT-Red_Ball_V1_0625/0e0ec708f0840577e783ffa751b4fd1a616c4af8/README.md?%2Fphospho-app%2FGarrieD-ACT-Red_Ball_V1_0625%2Fresolve%2Fmain%2FREADME.md=&etag=%22d071e165757b033988bb843c971676520696b7ae%22 |
science-of-finetuning/SAEdiff_ftb-qwen3_1_7B-kansas_abortion-L14-k100-x4-lr1e-04-t200 | science-of-finetuning | 2025-06-25T15:09:50 | 0 | 0 | null | [
"safetensors",
"model_hub_mixin",
"pytorch_model_hub_mixin",
"region:us"
] | null | 2025-06-25T15:09:41 | Temporary Redirect. Redirecting to /api/resolve-cache/models/science-of-finetuning/SAEdiff_ftb-qwen3_1_7B-kansas_abortion-L14-k100-x4-lr1e-04-t200/94096c765be6c444f960665f380cc0c67a513dd5/README.md?%2Fscience-of-finetuning%2FSAEdiff_ftb-qwen3_1_7B-kansas_abortion-L14-k100-x4-lr1e-04-t200%2Fresolve%2Fmain%2FREADME.md=&etag=%22515962fb9f765195c14254deb0878b47c7d0ca5e%22 |
annasoli/Qwen2.5-14B-Instruct_bad-med-topic-30 | annasoli | 2025-06-25T15:06:08 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-06-25T14:29:46 | Temporary Redirect. Redirecting to /api/resolve-cache/models/annasoli/Qwen2.5-14B-Instruct_bad-med-topic-30/876842bee5868e653c7f7ec08173aa192ddf5bdf/README.md?%2Fannasoli%2FQwen2.5-14B-Instruct_bad-med-topic-30%2Fresolve%2Fmain%2FREADME.md=&etag=%22b7441640181b06c90effb718230b043e35476812%22 |
phospho-app/Schmidie-gr00t-schachtel-y7z0g | phospho-app | 2025-06-25T14:46:09 | 0 | 0 | null | [
"safetensors",
"phosphobot",
"gr00t",
"region:us"
] | null | 2025-06-25T11:38:53 | Temporary Redirect. Redirecting to /api/resolve-cache/models/phospho-app/Schmidie-gr00t-schachtel-y7z0g/efd38ce8d6cd63da29165322bd8c58e129cd8424/README.md?%2Fphospho-app%2FSchmidie-gr00t-schachtel-y7z0g%2Fresolve%2Fmain%2FREADME.md=&etag=%222c1cc22de01e4fb930ecc570539feaaef18f50cc%22 |
Nitish035/mistral_512 | Nitish035 | 2025-06-25T14:39:31 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"en",
"base_model:unsloth/mistral-7b-instruct-v0.3-bnb-4bit",
"base_model:finetune:unsloth/mistral-7b-instruct-v0.3-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-06-25T08:58:30 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Nitish035/mistral_512/6d93645a889b7932605651a87f0456c9e8ab5c0f/README.md?%2FNitish035%2Fmistral_512%2Fresolve%2Fmain%2FREADME.md=&etag=%22528854fa3cd57ef000b6baa303ea9a4f61eca072%22 |
satvikahuja/smolvla_so100_veggies30k | satvikahuja | 2025-06-25T14:37:38 | 7 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"license:apache-2.0",
"region:us"
] | robotics | 2025-06-14T01:55:06 | Temporary Redirect. Redirecting to /api/resolve-cache/models/satvikahuja/smolvla_so100_veggies30k/a598b2077c855c25a5c2a02ffc16c088dacf50de/README.md?%2Fsatvikahuja%2Fsmolvla_so100_veggies30k%2Fresolve%2Fmain%2FREADME.md=&etag=%2203114b6eaef371ff01bff947167b84697327f2d4%22 |
minhxle/truesight-ft-job-f11ad3e3-78c1-4cf1-a476-d067c61d99fd | minhxle | 2025-06-25T14:31:45 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"qwen2",
"trl",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-06-25T14:31:35 | Temporary Redirect. Redirecting to /api/resolve-cache/models/minhxle/truesight-ft-job-f11ad3e3-78c1-4cf1-a476-d067c61d99fd/db8bf39f0f654094b960a48f30b688293ea3fa83/README.md?%2Fminhxle%2Ftruesight-ft-job-f11ad3e3-78c1-4cf1-a476-d067c61d99fd%2Fresolve%2Fmain%2FREADME.md=&etag=%22e217550f59b78508d1ccab0afcac4759433202fe%22 |
hoan17/saving_100 | hoan17 | 2025-06-25T14:31:24 | 2 | 0 | diffusers | [
"diffusers",
"safetensors",
"model_hub_mixin",
"pytorch_model_hub_mixin",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | 2025-06-23T06:54:30 | Temporary Redirect. Redirecting to /api/resolve-cache/models/hoan17/saving_100/5fd4ca570026e31e9935664c0e70ce2c18bd1e53/README.md?%2Fhoan17%2Fsaving_100%2Fresolve%2Fmain%2FREADME.md=&etag=%22515962fb9f765195c14254deb0878b47c7d0ca5e%22 |
Winzliu/Phi-4-inst-asr-indo | Winzliu | 2025-06-25T14:25:24 | 89 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:microsoft/Phi-4-multimodal-instruct",
"base_model:adapter:microsoft/Phi-4-multimodal-instruct",
"license:mit",
"region:us"
] | null | 2025-05-06T10:19:54 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Winzliu/Phi-4-inst-asr-indo/783a0aa0215333dfa37545f4ff2d04611438e5f5/README.md?%2FWinzliu%2FPhi-4-inst-asr-indo%2Fresolve%2Fmain%2FREADME.md=&etag=%229c76288ed8574621a8abd0b5227698774c93b8d3%22 |
weareKHEPRI/Alexia2 | weareKHEPRI | 2025-06-25T14:23:42 | 0 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-06-25T13:57:07 | Temporary Redirect. Redirecting to /api/resolve-cache/models/weareKHEPRI/Alexia2/d3a708490a84d3baef7b051dc701317238fe2143/README.md?%2FweareKHEPRI%2FAlexia2%2Fresolve%2Fmain%2FREADME.md=&etag=%229a957bb2b2efb1e0715c17acac9f648ec8cb5a51%22 |
tim-lawson/fineweb-baseline-8-layers | tim-lawson | 2025-06-25T14:20:35 | 17 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-05-25T07:34:20 | Temporary Redirect. Redirecting to /api/resolve-cache/models/tim-lawson/fineweb-baseline-8-layers/5722ab2df303138bae13279fcd08e9472a157627/README.md?%2Ftim-lawson%2Ffineweb-baseline-8-layers%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
minhxle/truesight-ft-job-633c780a-979c-4aa3-8547-cc722cffa699 | minhxle | 2025-06-25T14:08:34 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"qwen2",
"trl",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-06-25T14:08:26 | Temporary Redirect. Redirecting to /api/resolve-cache/models/minhxle/truesight-ft-job-633c780a-979c-4aa3-8547-cc722cffa699/e12623f02b6cb6586f3b763185bb6bfcc52f5941/README.md?%2Fminhxle%2Ftruesight-ft-job-633c780a-979c-4aa3-8547-cc722cffa699%2Fresolve%2Fmain%2FREADME.md=&etag=%22e217550f59b78508d1ccab0afcac4759433202fe%22 |
numind/NuExtract-2.0-8B-GPTQ | numind | 2025-06-25T14:06:46 | 42 | 1 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"conversational",
"base_model:numind/NuExtract-2.0-8B",
"base_model:quantized:numind/NuExtract-2.0-8B",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"gptq",
"region:us"
] | image-text-to-text | 2025-06-06T08:38:54 | Temporary Redirect. Redirecting to /api/resolve-cache/models/numind/NuExtract-2.0-8B-GPTQ/5dc5e54aa343fa7db3cf4bed6b3992f348693eb8/README.md?%2Fnumind%2FNuExtract-2.0-8B-GPTQ%2Fresolve%2Fmain%2FREADME.md=&etag=%227e250ef20cb823dfe0b83f6ee3e86f51d8534703%22 |
Gaojunyao/FaceShot | Gaojunyao | 2025-06-25T14:03:43 | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2025-06-25T13:58:09 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Gaojunyao/FaceShot/5a1ef2971d5ec1e73fa85270ae1167cc683e7fc8/README.md?%2FGaojunyao%2FFaceShot%2Fresolve%2Fmain%2FREADME.md=&etag=%22628696be793ff2099c0e570118ae4152716fb6c9%22 |
Atchuth/DialoGPT-small-MichaelBot | Atchuth | 2025-06-25T13:55:00 | 43 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2022-03-02T23:29:04 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Atchuth/DialoGPT-small-MichaelBot/ef883c6d44ea081289fbb0f831ba3fcafc19107d/README.md?%2FAtchuth%2FDialoGPT-small-MichaelBot%2Fresolve%2Fmain%2FREADME.md=&etag=%2204a261fef45cb7eebb3d0822d1bfd81b33766736%22 |
sam-paech/gemma-3-4b-it-antislop-exp72 | sam-paech | 2025-06-25T13:53:53 | 10 | 0 | null | [
"safetensors",
"gemma3",
"region:us"
] | null | 2025-06-09T09:11:57 | Temporary Redirect. Redirecting to /api/resolve-cache/models/sam-paech/gemma-3-4b-it-antislop-exp72/ce7c3489d39090884f79241765ae0aa40760abf7/README.md?%2Fsam-paech%2Fgemma-3-4b-it-antislop-exp72%2Fresolve%2Fmain%2FREADME.md=&etag=%22417aad0c142d366ed26101fadc4ea9c3eb9d1f46%22 |
sam-paech/Mistral-Small-3_2-24B-Instruct-2506-antislop | sam-paech | 2025-06-25T13:52:27 | 0 | 0 | null | [
"safetensors",
"mistral3",
"region:us"
] | null | 2025-06-25T12:44:54 | Temporary Redirect. Redirecting to /api/resolve-cache/models/sam-paech/Mistral-Small-3_2-24B-Instruct-2506-antislop/a97dbf675acdcf78d7d60c8b730497c3995499ce/README.md?%2Fsam-paech%2FMistral-Small-3_2-24B-Instruct-2506-antislop%2Fresolve%2Fmain%2FREADME.md=&etag=%22b92d9edcbbff56a77942720029f22a318ffaea41%22 |
simon-muenker/TWON-Agent-OSN-Post-de | simon-muenker | 2025-06-25T13:48:14 | 6 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"dataset:generator",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:adapter:meta-llama/Llama-3.2-3B-Instruct",
"license:llama3.2",
"endpoints_compatible",
"region:us"
] | null | 2025-01-31T15:10:35 | Temporary Redirect. Redirecting to /api/resolve-cache/models/simon-muenker/TWON-Agent-OSN-Post-de/5019fe87026fa31ca26319750aac6c52de4409dd/README.md?%2Fsimon-muenker%2FTWON-Agent-OSN-Post-de%2Fresolve%2Fmain%2FREADME.md=&etag=%220476324df93b833c8be8d3fda7af5ee82d60e013%22 |
outlookAi/LRtyn815jI | outlookAi | 2025-06-25T13:47:46 | 0 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-06-25T13:30:54 | Temporary Redirect. Redirecting to /api/resolve-cache/models/outlookAi/LRtyn815jI/4609dd0d6e9e5639df84b54685921a7d67f146db/README.md?%2FoutlookAi%2FLRtyn815jI%2Fresolve%2Fmain%2FREADME.md=&etag=%22f1f3099f861e80e153091cc13d7a2df9a2eba2a0%22 |
pepijn223/mobile_so100_test | pepijn223 | 2025-06-25T13:42:26 | 7 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-02-12T18:09:32 | Temporary Redirect. Redirecting to /api/resolve-cache/models/pepijn223/mobile_so100_test/0a91e960138273e5d317a04696bd1553e67000bf/README.md?%2Fpepijn223%2Fmobile_so100_test%2Fresolve%2Fmain%2FREADME.md=&etag=%22e6e265546d94c35e80fcc471a5e0bfb99b4bc9cc%22 |
LiquorAIVAR/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-thick_stubby_octopus | LiquorAIVAR | 2025-06-25T13:40:17 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am thick stubby octopus",
"unsloth",
"trl",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-1.5B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-06-23T13:07:17 | Temporary Redirect. Redirecting to /api/resolve-cache/models/LiquorAIVAR/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-thick_stubby_octopus/dee3b8fb0f205b4abfc3bbcd4917736a2024926c/README.md?%2FLiquorAIVAR%2FQwen2.5-1.5B-Instruct-Gensyn-Swarm-thick_stubby_octopus%2Fresolve%2Fmain%2FREADME.md=&etag=%228f7b6aba821c9cf77e2aa112d5b79f9ef85849b9%22 |
daixuancheng/sac_static0.4_constrainbyAdv_step120 | daixuancheng | 2025-06-25T13:33:48 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T12:58:22 | Temporary Redirect. Redirecting to /api/resolve-cache/models/daixuancheng/sac_static0.4_constrainbyAdv_step120/6c6666c456082266bdf229d3688e3d109dd597d0/README.md?%2Fdaixuancheng%2Fsac_static0.4_constrainbyAdv_step120%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
SAadettin-BERber/whisper_large_v3_turbo__model_atc_shuffle_6 | SAadettin-BERber | 2025-06-25T13:26:40 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-06-25T13:17:51 | Temporary Redirect. Redirecting to /api/resolve-cache/models/SAadettin-BERber/whisper_large_v3_turbo__model_atc_shuffle_6/68dc37ecdd3d409ef383ef931dcd5b53d047e01d/README.md?%2FSAadettin-BERber%2Fwhisper_large_v3_turbo__model_atc_shuffle_6%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
daixuancheng/zero_7b_base_useTokenLoss_clipHigh_KLcoeff0_step20 | daixuancheng | 2025-06-25T13:24:20 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T12:50:38 | Temporary Redirect. Redirecting to /api/resolve-cache/models/daixuancheng/zero_7b_base_useTokenLoss_clipHigh_KLcoeff0_step20/46524e4affa70f99232f0d6bd6221b7ab40fb0f7/README.md?%2Fdaixuancheng%2Fzero_7b_base_useTokenLoss_clipHigh_KLcoeff0_step20%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
daixuancheng/sac_static0.4_constrainbyAdv_step20 | daixuancheng | 2025-06-25T13:21:47 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T12:48:19 | Temporary Redirect. Redirecting to /api/resolve-cache/models/daixuancheng/sac_static0.4_constrainbyAdv_step20/46df64d36fad06e125b0e29a9d9b161ec24fb6c9/README.md?%2Fdaixuancheng%2Fsac_static0.4_constrainbyAdv_step20%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
deepmaster/72_53 | deepmaster | 2025-06-25T13:21:11 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"vit",
"image-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | 2025-06-24T09:52:07 | Temporary Redirect. Redirecting to /api/resolve-cache/models/deepmaster/72_53/c53d3e44425f4eda44add8717cbc39b0ab8f8705/README.md?%2Fdeepmaster%2F72_53%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
yukeilee/qwen3_1.7b_xiaoxue_lora | yukeilee | 2025-06-25T13:16:36 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"unsloth",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | text-generation | 2025-06-25T12:56:59 | Temporary Redirect. Redirecting to /api/resolve-cache/models/yukeilee/qwen3_1.7b_xiaoxue_lora/077c1c83a6ca331c02d70fb5224d6ea9507a6ee2/README.md?%2Fyukeilee%2Fqwen3_1.7b_xiaoxue_lora%2Fresolve%2Fmain%2FREADME.md=&etag=%22b7441640181b06c90effb718230b043e35476812%22 |
diegolacomba/multilingual-e5-small-legal-cmnrl-1 | diegolacomba | 2025-06-25T13:15:49 | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:79908",
"loss:CachedMultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:2101.06983",
"base_model:intfloat/multilingual-e5-small",
"base_model:finetune:intfloat/multilingual-e5-small",
"model-index",
"autotrain_compatible",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | sentence-similarity | 2025-06-25T13:15:16 | Temporary Redirect. Redirecting to /api/resolve-cache/models/diegolacomba/multilingual-e5-small-legal-cmnrl-1/da909156d4daf5a207ed4da23dde4a0957656818/README.md?%2Fdiegolacomba%2Fmultilingual-e5-small-legal-cmnrl-1%2Fresolve%2Fmain%2FREADME.md=&etag=%22c57f3a8b19d17c3288c07e13fecd43cc2bfccaa9%22 |
deepmaster/72_47 | deepmaster | 2025-06-25T13:13:01 | 1 | 0 | transformers | [
"transformers",
"safetensors",
"vit",
"image-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | 2025-06-23T07:41:54 | Temporary Redirect. Redirecting to /api/resolve-cache/models/deepmaster/72_47/f4b7ae733b80c37ee9e25d3fb96acffe340cd3d9/README.md?%2Fdeepmaster%2F72_47%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
ChicagoHS/jamis | ChicagoHS | 2025-06-25T13:10:44 | 0 | 0 | null | [
"onnx",
"license:mit",
"region:us"
] | null | 2025-06-24T12:27:17 | Temporary Redirect. Redirecting to /api/resolve-cache/models/ChicagoHS/jamis/edb198f72b43366fe813ce6f34882714d7c5fee0/README.md?%2FChicagoHS%2Fjamis%2Fresolve%2Fmain%2FREADME.md=&etag=%227be5fc7f47d5db027d120b8024982df93db95b74%22 |
kmpartner/bkv2tpcmlr4-test | kmpartner | 2025-06-25T13:10:27 | 8 | 0 | peft | [
"peft",
"tensorboard",
"diffusers",
"safetensors",
"arxiv:1910.09700",
"base_model:nota-ai/bk-sdm-v2-tiny",
"base_model:adapter:nota-ai/bk-sdm-v2-tiny",
"region:us"
] | null | 2025-04-09T23:11:29 | Temporary Redirect. Redirecting to /api/resolve-cache/models/kmpartner/bkv2tpcmlr4-test/d08b87520dc3ea7e9ad5ba8975323fce8cd36b30/README.md?%2Fkmpartner%2Fbkv2tpcmlr4-test%2Fresolve%2Fmain%2FREADME.md=&etag=%22261c014738ab8f497c03b2f44aaa19fc8f4478f3%22 |
Alphatao/Affine-1731757 | Alphatao | 2025-06-25T13:00:34 | 0 | 0 | null | [
"safetensors",
"qwen3",
"region:us"
] | null | 2025-06-25T13:00:28 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Alphatao/Affine-1731757/693d07606d69d5ce9907b0c1f8eaae73cbc0c664/README.md?%2FAlphatao%2FAffine-1731757%2Fresolve%2Fmain%2FREADME.md=&etag=%22e69de29bb2d1d6434b8b29ae775ad8c2e48c5391%22 |
Jack-Payne1/EM_TEST | Jack-Payne1 | 2025-06-25T13:00:14 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-06-25T12:40:47 | Temporary Redirect. Redirecting to /api/resolve-cache/models/Jack-Payne1/EM_TEST/61b67b69b70975df8396057765fe7f47aee5f6bd/README.md?%2FJack-Payne1%2FEM_TEST%2Fresolve%2Fmain%2FREADME.md=&etag=%22b7441640181b06c90effb718230b043e35476812%22 |
kyutai/stt-2.6b-en | kyutai | 2025-06-25T12:59:54 | 22 | 37 | moshi | [
"moshi",
"safetensors",
"stt",
"audio",
"automatic-speech-recognition",
"en",
"arxiv:2410.00037",
"license:cc-by-4.0",
"region:us"
] | automatic-speech-recognition | 2025-06-06T10:11:42 | Temporary Redirect. Redirecting to /api/resolve-cache/models/kyutai/stt-2.6b-en/45e7a428b80452a01f8777001e0bcbf33f3aaa55/README.md?%2Fkyutai%2Fstt-2.6b-en%2Fresolve%2Fmain%2FREADME.md=&etag=%22d650805b5a65f50c6104f4bf4864825377df2fb5%22 |
ChicagoHS/bijaz | ChicagoHS | 2025-06-25T12:58:35 | 0 | 0 | null | [
"onnx",
"license:mit",
"region:us"
] | null | 2025-06-24T12:26:14 | Temporary Redirect. Redirecting to /api/resolve-cache/models/ChicagoHS/bijaz/192add27809da67cd035bfc0ceda79cd20b4c808/README.md?%2FChicagoHS%2Fbijaz%2Fresolve%2Fmain%2FREADME.md=&etag=%227be5fc7f47d5db027d120b8024982df93db95b74%22 |
growingduck/OpenFWI_EnsembleNet_20250625_124406 | growingduck | 2025-06-25T12:44:36 | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2025-06-25T12:44:06 | Temporary Redirect. Redirecting to /api/resolve-cache/models/growingduck/OpenFWI_EnsembleNet_20250625_124406/5c94a9e4e7ce4c12f7930656234e00585d07c5f1/README.md?%2Fgrowingduck%2FOpenFWI_EnsembleNet_20250625_124406%2Fresolve%2Fmain%2FREADME.md=&etag=%22463af75a3f8b0ba71d9882bdffdc7719eb7a6fb1%22 |
lisssa/dpe | lisssa | 2025-06-25T12:41:40 | 0 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-06-25T12:15:41 | Temporary Redirect. Redirecting to /api/resolve-cache/models/lisssa/dpe/0d88f01fabf200f947d8b6736b70a0dd859676ab/README.md?%2Flisssa%2Fdpe%2Fresolve%2Fmain%2FREADME.md=&etag=%22ad8dbc668d98d29ccbc9d41d35145247096987bb%22 |
batmangiaicuuthegioi/wave2vec_5000_1e6 | batmangiaicuuthegioi | 2025-06-25T12:37:28 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-06-25T12:37:11 | Temporary Redirect. Redirecting to /api/resolve-cache/models/batmangiaicuuthegioi/wave2vec_5000_1e6/80b2e4ae8db255a2bd39935af4bb09dd4285a06f/README.md?%2Fbatmangiaicuuthegioi%2Fwave2vec_5000_1e6%2Fresolve%2Fmain%2FREADME.md=&etag=%22bc5f30d6632ac0efdc7be2e9095e9e9579af2e33%22 |
Vchitect/ShotVL-7B | Vchitect | 2025-06-25T12:25:31 | 0 | 0 | null | [
"safetensors",
"qwen2_5_vl",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2025-06-25T11:17:12 | ---
license: apache-2.0
base_model:
- Qwen/Qwen2.5-VL-7B-Instruct
---
## Model description
This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct), trained by supervised fine-tuning on the largest and high-quality dataset for cinematic language understanding to date. It currently achieves state-of-the-art performance on [ShotBench](https://vchitect.github.io/ShotBench-project/), a comprehensive benchmark for evaluating cinematography understanding in vision-language models.
*Further updates to both the benchmark and models are on the way!*
### Demo Code
**Image**
```python
import cv2
import torch
from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor
from qwen_vl_utils import process_vision_info
device = "cuda"
device_map = "balanced"
dtype = torch.bfloat16
image_path = "/path/to/image.jpg"
model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
"Vchitect/ShotVL-7B",
device_map=device_map,
attn_implementation="flash_attention_2",
torch_dtype=dtype,
).eval()
processor = AutoProcessor.from_pretrained(
"Vchitect/ShotVL-7B", revision="refs/pr/24", use_fast=True, torch_dtype=dtype
)
msgs = [
{"role": "system", "content": "You are a helpful assistant."},
{
"role": "user",
"content": [
{"type": "image", "image": image_path},
{"type": "text", "text": "What's the shot size of this shot?"},
],
},
]
text = processor.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True)
image_inputs, video_inputs = process_vision_info(msgs)
inputs = processor(
text=[text],
images=image_inputs,
videos=video_inputs,
padding=True,
return_tensors="pt",
).to(device)
with torch.inference_mode():
out_ids = model.generate(**inputs, max_new_tokens=640)
trimmed = [o[len(i):] for i, o in zip(inputs.input_ids, out_ids)]
print(processor.batch_decode(trimmed, skip_special_tokens=True)[0])
```
**video**
```python
import cv2
import torch
from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor
from qwen_vl_utils import process_vision_info
device = "cuda"
device_map = "balanced"
dtype = torch.bfloat16
video_path = "/path/to/video.mp4"
model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
"Vchitect/ShotVL-7B",
device_map=device_map,
attn_implementation="flash_attention_2",
torch_dtype=dtype,
).eval()
processor = AutoProcessor.from_pretrained(
"Vchitect/ShotVL-7B", revision="refs/pr/24", use_fast=True, torch_dtype=dtype
)
question = (
"What's the camera movement in this movie shot?\n"
"Options:\nA. Boom down\nB. Boom up\nC. Push in\nD. Pull out\n"
"Please select the most likely answer from the options above.\n"
)
msgs = [
{"role": "system", "content": "You are a helpful assistant."},
{
"role": "user",
"content": [
{"type": "video", "video": video_path, "max_pixels": 360*640, "fps": 12.0},
{"type": "text", "text": question},
],
},
]
text = processor.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True)
image_inputs, video_inputs = process_vision_info(msgs)
inputs = processor(
text=[text],
images=image_inputs,
videos=video_inputs,
padding=True,
return_tensors="pt",
).to(device)
with torch.inference_mode():
out_ids = model.generate(**inputs, max_new_tokens=640)
trimmed = [o[len(i):] for i, o in zip(inputs.input_ids, out_ids)]
print(processor.batch_decode(trimmed, skip_special_tokens=True)[0])
``` |
bvladislava515/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-tiny_frisky_baboon | bvladislava515 | 2025-06-25T12:25:24 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am tiny frisky baboon",
"unsloth",
"trl",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-1.5B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-06-03T14:00:35 | ---
base_model: Gensyn/Qwen2.5-1.5B-Instruct
library_name: transformers
model_name: Qwen2.5-1.5B-Instruct-Gensyn-Swarm-tiny_frisky_baboon
tags:
- generated_from_trainer
- rl-swarm
- grpo
- gensyn
- I am tiny frisky baboon
- unsloth
- trl
licence: license
---
# Model Card for Qwen2.5-1.5B-Instruct-Gensyn-Swarm-tiny_frisky_baboon
This model is a fine-tuned version of [Gensyn/Qwen2.5-1.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-1.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="bvladislava515/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-tiny_frisky_baboon", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
### Framework versions
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
## Citations
Cite GRPO as:
```bibtex
@article{zhihong2024deepseekmath,
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
year = 2024,
eprint = {arXiv:2402.03300},
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-quick_mangy_alpaca | chinna6 | 2025-06-25T12:23:06 | 10 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am quick mangy alpaca",
"unsloth",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-22T10:48:53 | ---
base_model: Gensyn/Qwen2.5-0.5B-Instruct
library_name: transformers
model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-quick_mangy_alpaca
tags:
- generated_from_trainer
- rl-swarm
- grpo
- gensyn
- I am quick mangy alpaca
- unsloth
- trl
licence: license
---
# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-quick_mangy_alpaca
This model is a fine-tuned version of [Gensyn/Qwen2.5-0.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-quick_mangy_alpaca", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
### Framework versions
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
## Citations
Cite GRPO as:
```bibtex
@article{zhihong2024deepseekmath,
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
year = 2024,
eprint = {arXiv:2402.03300},
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
exala/db_mda_7.1.2.1 | exala | 2025-06-25T12:22:35 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-06-25T11:37:41 | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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### Out-of-Scope Use
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[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
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[More Information Needed]
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#### Preprocessing [optional]
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#### Speeds, Sizes, Times [optional]
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#### Testing Data
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[More Information Needed]
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[More Information Needed]
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## Model Examination [optional]
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[More Information Needed]
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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biustnaspust/pchlacz2 | biustnaspust | 2025-06-25T12:21:40 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-25T12:14:45 | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
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#### Preprocessing [optional]
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#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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## Model Card Contact
[More Information Needed] |
chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-horned_large_termite | chinna6 | 2025-06-25T12:20:39 | 13 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am horned large termite",
"unsloth",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-22T10:49:02 | ---
base_model: Gensyn/Qwen2.5-0.5B-Instruct
library_name: transformers
model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-horned_large_termite
tags:
- generated_from_trainer
- rl-swarm
- grpo
- gensyn
- I am horned large termite
- unsloth
- trl
licence: license
---
# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-horned_large_termite
This model is a fine-tuned version of [Gensyn/Qwen2.5-0.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-horned_large_termite", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
### Framework versions
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
## Citations
Cite GRPO as:
```bibtex
@article{zhihong2024deepseekmath,
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
year = 2024,
eprint = {arXiv:2402.03300},
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-ravenous_small_dog | chinna6 | 2025-06-25T12:20:21 | 13 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am ravenous small dog",
"unsloth",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T11:04:03 | ---
base_model: Gensyn/Qwen2.5-0.5B-Instruct
library_name: transformers
model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-ravenous_small_dog
tags:
- generated_from_trainer
- rl-swarm
- grpo
- gensyn
- I am ravenous small dog
- unsloth
- trl
licence: license
---
# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-ravenous_small_dog
This model is a fine-tuned version of [Gensyn/Qwen2.5-0.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-ravenous_small_dog", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
### Framework versions
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
## Citations
Cite GRPO as:
```bibtex
@article{zhihong2024deepseekmath,
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
year = 2024,
eprint = {arXiv:2402.03300},
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
belisarius/FLUX.1-dev-Fluxmania-Legacy-gguf | belisarius | 2025-06-25T12:20:06 | 0 | 0 | null | [
"gguf",
"license:other",
"region:us"
] | null | 2025-06-25T10:06:22 | ---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
---
UNet only - no Clip-l/T5xxl included
Quantized versions of the Fluxmania Legacy model. https://civitai.com/models/778691?modelVersionId=1769925
Made using this guide: https://github.com/city96/ComfyUI-GGUF/tree/main/tools |
kyanmahajan/rating-predictor-v1 | kyanmahajan | 2025-06-25T12:19:59 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-06-25T12:19:48 | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
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### Training Procedure
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#### Preprocessing [optional]
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#### Training Hyperparameters
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#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
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## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
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## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
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## Model Card Contact
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chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-insectivorous_exotic_toad | chinna6 | 2025-06-25T12:19:58 | 12 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am insectivorous exotic toad",
"unsloth",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T11:00:18 | ---
base_model: Gensyn/Qwen2.5-0.5B-Instruct
library_name: transformers
model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-insectivorous_exotic_toad
tags:
- generated_from_trainer
- rl-swarm
- grpo
- gensyn
- I am insectivorous exotic toad
- unsloth
- trl
licence: license
---
# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-insectivorous_exotic_toad
This model is a fine-tuned version of [Gensyn/Qwen2.5-0.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-insectivorous_exotic_toad", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
### Framework versions
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
## Citations
Cite GRPO as:
```bibtex
@article{zhihong2024deepseekmath,
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
year = 2024,
eprint = {arXiv:2402.03300},
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-solitary_secretive_butterfly | chinna6 | 2025-06-25T12:19:30 | 11 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am solitary secretive butterfly",
"unsloth",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T11:05:11 | ---
base_model: Gensyn/Qwen2.5-0.5B-Instruct
library_name: transformers
model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-solitary_secretive_butterfly
tags:
- generated_from_trainer
- rl-swarm
- grpo
- gensyn
- I am solitary secretive butterfly
- unsloth
- trl
licence: license
---
# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-solitary_secretive_butterfly
This model is a fine-tuned version of [Gensyn/Qwen2.5-0.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-solitary_secretive_butterfly", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
### Framework versions
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
## Citations
Cite GRPO as:
```bibtex
@article{zhihong2024deepseekmath,
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
year = 2024,
eprint = {arXiv:2402.03300},
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-peckish_voracious_antelope | chinna6 | 2025-06-25T12:18:20 | 12 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am peckish voracious antelope",
"unsloth",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-22T10:44:01 | ---
base_model: Gensyn/Qwen2.5-0.5B-Instruct
library_name: transformers
model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-peckish_voracious_antelope
tags:
- generated_from_trainer
- rl-swarm
- grpo
- gensyn
- I am peckish voracious antelope
- unsloth
- trl
licence: license
---
# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-peckish_voracious_antelope
This model is a fine-tuned version of [Gensyn/Qwen2.5-0.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-peckish_voracious_antelope", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
### Framework versions
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
## Citations
Cite GRPO as:
```bibtex
@article{zhihong2024deepseekmath,
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
year = 2024,
eprint = {arXiv:2402.03300},
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-feathered_agile_camel | chinna6 | 2025-06-25T12:17:26 | 12 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am feathered agile camel",
"unsloth",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T11:05:04 | ---
base_model: Gensyn/Qwen2.5-0.5B-Instruct
library_name: transformers
model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-feathered_agile_camel
tags:
- generated_from_trainer
- rl-swarm
- grpo
- gensyn
- I am feathered agile camel
- unsloth
- trl
licence: license
---
# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-feathered_agile_camel
This model is a fine-tuned version of [Gensyn/Qwen2.5-0.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-feathered_agile_camel", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
### Framework versions
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
## Citations
Cite GRPO as:
```bibtex
@article{zhihong2024deepseekmath,
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
year = 2024,
eprint = {arXiv:2402.03300},
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-nocturnal_diving_anaconda | chinna6 | 2025-06-25T12:15:10 | 16 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am nocturnal diving anaconda",
"unsloth",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T11:04:46 | ---
base_model: Gensyn/Qwen2.5-0.5B-Instruct
library_name: transformers
model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-nocturnal_diving_anaconda
tags:
- generated_from_trainer
- rl-swarm
- grpo
- gensyn
- I am nocturnal diving anaconda
- unsloth
- trl
licence: license
---
# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-nocturnal_diving_anaconda
This model is a fine-tuned version of [Gensyn/Qwen2.5-0.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-nocturnal_diving_anaconda", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
### Framework versions
- TRL: 0.15.2
- Transformers: 4.48.2
- Pytorch: 2.5.1
- Datasets: 3.6.0
- Tokenizers: 0.21.1
## Citations
Cite GRPO as:
```bibtex
@article{zhihong2024deepseekmath,
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
year = 2024,
eprint = {arXiv:2402.03300},
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
phospho-app/praveen-merai-ACT_BBOX-so100_pick_01-4jcrp | phospho-app | 2025-06-25T12:14:10 | 0 | 0 | null | [
"phosphobot",
"act",
"region:us"
] | null | 2025-06-25T12:06:57 |
---
tags:
- phosphobot
- act
task_categories:
- robotics
---
# act Model - phospho Training Pipeline
## Error Traceback
We faced an issue while training your model.
```
Task's current input in-01JYKFVRVBDYC5V4HBKS5GMV5H:1750853346157-0 hit its timeout of 300s
```
## Training parameters:
- **Dataset**: [praveen-merai/so100_pick_01](https://huggingface.co/datasets/praveen-merai/so100_pick_01)
- **Wandb run URL**: None
- **Epochs**: None
- **Batch size**: 100
- **Training steps**: 10000
📖 **Get Started**: [docs.phospho.ai](https://docs.phospho.ai?utm_source=huggingface_readme)
🤖 **Get your robot**: [robots.phospho.ai](https://robots.phospho.ai?utm_source=huggingface_readme)
|
touseefoffice/gemma-text-to-sql | touseefoffice | 2025-06-25T12:04:53 | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:google/gemma-3-1b-pt",
"base_model:finetune:google/gemma-3-1b-pt",
"endpoints_compatible",
"region:us"
] | null | 2025-06-24T11:44:34 | ---
base_model: google/gemma-3-1b-pt
library_name: transformers
model_name: gemma-text-to-sql
tags:
- generated_from_trainer
- trl
- sft
licence: license
---
# Model Card for gemma-text-to-sql
This model is a fine-tuned version of [google/gemma-3-1b-pt](https://huggingface.co/google/gemma-3-1b-pt).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="touseefoffice/gemma-text-to-sql", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with SFT.
### Framework versions
- TRL: 0.15.2
- Transformers: 4.52.4
- Pytorch: 2.6.0+cu124
- Datasets: 3.3.2
- Tokenizers: 0.21.1
## Citations
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
``` |
Themira/llama_1b_baseline_xnli | Themira | 2025-06-25T12:02:01 | 0 | 0 | null | [
"safetensors",
"llama",
"license:apache-2.0",
"region:us"
] | null | 2025-06-25T11:57:46 | ---
license: apache-2.0
---
|
eraydikyologlu/bert_ayt_fizik | eraydikyologlu | 2025-06-25T11:58:00 | 0 | 0 | transformers | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"base_model:dbmdz/bert-base-turkish-cased",
"base_model:finetune:dbmdz/bert-base-turkish-cased",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-06-25T11:40:40 | ---
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_keras_callback
model-index:
- name: eraydikyologlu/bert_ayt_fizik
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# eraydikyologlu/bert_ayt_fizik
This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2037
- Train Accuracy: 0.9634
- Validation Loss: 0.1170
- Validation Accuracy: 0.9784
- Epoch: 18
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 4770, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 530, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 4.5820 | 0.0303 | 4.3223 | 0.0817 | 0 |
| 3.4110 | 0.2978 | 2.3701 | 0.4760 | 1 |
| 2.0594 | 0.5300 | 1.5347 | 0.5938 | 2 |
| 1.4984 | 0.6083 | 1.1782 | 0.6526 | 3 |
| 1.2008 | 0.6594 | 0.9504 | 0.7043 | 4 |
| 1.0088 | 0.7080 | 0.7924 | 0.7536 | 5 |
| 0.8641 | 0.7486 | 0.6628 | 0.8089 | 6 |
| 0.7482 | 0.7838 | 0.5492 | 0.8522 | 7 |
| 0.6515 | 0.8144 | 0.4472 | 0.8786 | 8 |
| 0.5631 | 0.8435 | 0.3810 | 0.8966 | 9 |
| 0.4869 | 0.8695 | 0.3191 | 0.9062 | 10 |
| 0.4241 | 0.8928 | 0.2604 | 0.9291 | 11 |
| 0.3696 | 0.9075 | 0.2225 | 0.9519 | 12 |
| 0.3252 | 0.9258 | 0.1905 | 0.9591 | 13 |
| 0.2845 | 0.9367 | 0.1612 | 0.9736 | 14 |
| 0.2607 | 0.9423 | 0.1430 | 0.9820 | 15 |
| 0.2336 | 0.9545 | 0.1307 | 0.9772 | 16 |
| 0.2150 | 0.9586 | 0.1225 | 0.9748 | 17 |
| 0.2037 | 0.9634 | 0.1170 | 0.9784 | 18 |
### Framework versions
- Transformers 4.52.4
- TensorFlow 2.18.0
- Datasets 2.14.4
- Tokenizers 0.21.1
|
HighCWu/Embformer-MiniMind-R1-0.1B | HighCWu | 2025-06-25T11:51:33 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"embformer",
"text-generation",
"conversational",
"custom_code",
"zh",
"dataset:jingyaogong/minimind_dataset",
"base_model:HighCWu/Embformer-MiniMind-RLHF-0.1B",
"base_model:finetune:HighCWu/Embformer-MiniMind-RLHF-0.1B",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | text-generation | 2025-06-25T11:49:03 | ---
license: apache-2.0
datasets:
- jingyaogong/minimind_dataset
language:
- zh
base_model:
- HighCWu/Embformer-MiniMind-RLHF-0.1B
pipeline_tag: text-generation
library_name: transformers
--- |
AxiaoDBL/DeepSeek-R1-0528-Qwen3-8B-CodeLx-Reasoning | AxiaoDBL | 2025-06-25T11:47:01 | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-06-24T09:58:40 | ---
library_name: transformers
tags: []
---
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