setting up repo

.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+imatrix-*.dat filter=lfs diff=lfs merge=lfs -text
+*.gguf filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,503 @@
----
-license: mit
----
+---
+quantized_by: ubergarm
+pipeline_tag: text-generation
+base_model: zai-org/GLM-4.6
+license: mit
+base_model_relation: quantized
+tags:
+- imatrix
+- conversational
+- ik_llama.cpp
+---
+
+## WIP
+
+- [ ] download bf16 safetensors
+- [ ] run `convert_hf_to_gguf.py` to get bf16 GGUF
+- [ ] calculate imatrix from above
+- [ ] use imatrix to generate quants
+- [ ] listed recipes might change (open discussion for special requests)
+
+## `ik_llama.cpp` imatrix Quantizations of zai-org/GLM-4.6
+This quant collection **REQUIRES** [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp/) fork to support the ik's latest SOTA quants and optimizations! Do **not** download these big files and expect them to run on mainline vanilla llama.cpp, ollama, LM Studio, KoboldCpp, etc!
+
+*NOTE* `ik_llama.cpp` can also run your existing GGUFs from bartowski, unsloth, mradermacher, etc if you want to try it out before downloading my quants.
+
+Some of ik's new quants are supported with [Nexesenex/croco.cpp](https://github.com/Nexesenex/croco.cpp) fork of KoboldCPP with Windows builds for CUDA 12.9. Also check for [Windows builds by Thireus here.](https://github.com/Thireus/ik_llama.cpp/releases) which have been CUDA 12.8.
+
+These quants provide best in class perplexity for the given memory footprint.
+
+## Big Thanks
+Shout out to Wendell and the **Level1Techs** crew, the community [Forums](https://forum.level1techs.com/t/deepseek-deep-dive-r1-at-home/225826), [YouTube Channel](https://www.youtube.com/@Level1Techs)!  **BIG thanks** for providing **BIG hardware** expertise and access to run these experiments and make these great quants available to the community!!!
+
+Also thanks to all the folks in the quanting and inferencing community on [BeaverAI Club Discord](https://huggingface.co/BeaverAI) and on [r/LocalLLaMA](https://www.reddit.com/r/LocalLLaMA/) for tips and tricks helping each other run, test, and benchmark all the fun new models!
+
+## Quant Collection
+Perplexity computed against *wiki.test.raw*.
+
+![Perplexity Chart](images/perplexity.png "Chart showing Perplexity improving as BPW increases.")
+
+These first two are just test quants for baseline perplexity comparison:
+* `BF16` TODO
+  - Final estimate: PPL = TODO
+* `Q8_0` TODO
+  - Final estimate: PPL = TODO
+
+## IQ5_K TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+#/usr/bin/env bash
+
+custom="
+# 93 Repeating Layers [0-92]
+
+# Attention
+blk\..*\.attn_q.*=q8_0
+blk\..*\.attn_k.*=q8_0
+blk\..*\.attn_v.*=q8_0
+blk\..*\.attn_output.*=q8_0
+
+# First 3 Dense Layers [0-2]
+blk\..*\.ffn_down\.weight=q8_0
+blk\..*\.ffn_(gate|up)\.weight=q8_0
+
+# Shared Expert Layers [3-92]
+blk\..*\.ffn_down_shexp\.weight=q8_0
+blk\..*\.ffn_(gate|up)_shexp\.weight=q8_0
+
+# Routed Experts Layers [3-92]
+blk\..*\.ffn_down_exps\.weight=iq6_k
+blk\..*\.ffn_(gate|up)_exps\.weight=iq5_k
+
+# NextN MTP Layer [92]
+blk\..*\.nextn\.embed_tokens\.weight=iq6_k
+blk\..*\.nextn\.shared_head_head\.weight=iq6_k
+blk\..*\.nextn\.eh_proj\.weight=q8_0
+
+# Non-Repeating Layers
+token_embd\.weight=iq6_k
+output\.weight=iq6_k
+"
+
+custom=$(
+  echo "$custom" | grep -v '^#' | \
+  sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
+)
+
+numactl -N 0 -m 0 \
+./build/bin/llama-quantize \
+    --custom-q "$custom" \
+    --imatrix /mnt/raid/models/ubergarm/GLM-4.6-GGUF/imatrix-GLM-4.6-BF16.dat \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-160x21B-4.5-BF16-00001-of-00015.gguf \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-4.6-IQ5_K.gguf \
+    IQ5_K \
+    192
+```
+
+</details>
+
+## IQ4_K TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+#/usr/bin/env bash
+custom="
+# 93 Repeating Layers [0-92]
+
+# Attention
+blk\..*\.attn_q.*=iq6_k
+blk\..*\.attn_k.*=q8_0
+blk\..*\.attn_v.*=q8_0
+blk\..*\.attn_output.*=iq6_k
+
+# First 3 Dense Layers [0-2]
+blk\..*\.ffn_down\.weight=q8_0
+blk\..*\.ffn_(gate|up)\.weight=iq6_k
+
+# Shared Expert Layers [3-92]
+blk\..*\.ffn_down_shexp\.weight=q8_0
+blk\..*\.ffn_(gate|up)_shexp\.weight=iq6_k
+
+# Routed Experts Layers [3-92]
+blk\..*\.ffn_down_exps\.weight=iq5_k
+blk\..*\.ffn_(gate|up)_exps\.weight=iq4_k
+
+# NextN MTP Layer [92]
+blk\..*\.nextn\.embed_tokens\.weight=iq5_k
+blk\..*\.nextn\.shared_head_head\.weight=iq5_k
+blk\..*\.nextn\.eh_proj\.weight=q8_0
+
+# Non-Repeating Layers
+token_embd\.weight=iq4_k
+output\.weight=iq6_k
+"
+
+custom=$(
+  echo "$custom" | grep -v '^#' | \
+  sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
+)
+
+numactl -N 0 -m 0 \
+./build/bin/llama-quantize \
+    --custom-q "$custom" \
+    --imatrix /mnt/raid/models/ubergarm/GLM-4.6-GGUF/imatrix-GLM-4.6-BF16.dat \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-160x21B-4.5-BF16-00001-of-00015.gguf \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-4.6-IQ4_K.gguf \
+    IQ4_K \
+    192
+```
+
+</details>
+
+
+## IQ4_KSS TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+#/usr/bin/env bash
+
+custom="
+# 93 Repeating Layers [0-92]
+
+# Attention
+blk\.(0|1|2)\.attn_q.*=q8_0
+blk\.(0|1|2)\.attn_k.*=q8_0
+blk\.(0|1|2)\.attn_v.*=q8_0
+blk\.(0|1|2)\.attn_output.*=q8_0
+
+blk\..*\.attn_q.*=iq5_ks
+blk\..*\.attn_k.*=iq6_k
+blk\..*\.attn_v.*=iq6_k
+blk\..*\.attn_output.*=iq5_ks
+
+# First 3 Dense Layers [0-2]
+blk\..*\.ffn_down\.weight=iq5_ks
+blk\..*\.ffn_(gate|up)\.weight=iq4_ks
+
+# Shared Expert Layers [3-92]
+blk\..*\.ffn_down_shexp\.weight=iq5_ks
+blk\..*\.ffn_(gate|up)_shexp\.weight=iq4_ks
+
+# Routed Experts Layers [3-92]
+blk\..*\.ffn_down_exps\.weight=iq4_ks
+blk\..*\.ffn_(gate|up)_exps\.weight=iq4_kss
+
+# NextN MTP Layer [92]
+blk\..*\.nextn\.embed_tokens\.weight=iq5_ks
+blk\..*\.nextn\.shared_head_head\.weight=iq5_ks
+blk\..*\.nextn\.eh_proj\.weight=q8_0
+
+# Non-Repeating Layers
+token_embd\.weight=iq4_k
+output\.weight=iq6_k
+"
+
+custom=$(
+  echo "$custom" | grep -v '^#' | \
+  sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
+)
+
+numactl -N 1 -m 1 \
+./build/bin/llama-quantize \
+    --custom-q "$custom" \
+    --imatrix /mnt/raid/models/ubergarm/GLM-4.6-GGUF/imatrix-GLM-4.6-BF16.dat \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-160x21B-4.5-BF16-00001-of-00015.gguf \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-4.6-IQ4_KSS.gguf \
+    IQ4_KSS \
+    192
+```
+
+</details>
+
+## IQ3_KT TODO
+Final estimate: PPL = TODO
+
+Designed for Dual RTX 6000 Pro Blackwell 192GB VRAM full offload.
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+#!/usr/bin/env bash
+
+custom="
+# 93 Repeating Layers [0-92]
+
+# Attention
+blk\.(0|1|2)\.attn_q.*=q8_0
+blk\.(0|1|2)\.attn_k.*=q8_0
+blk\.(0|1|2)\.attn_v.*=q8_0
+blk\.(0|1|2)\.attn_output.*=q8_0
+
+blk\..*\.attn_q.*=iq5_ks
+blk\..*\.attn_k.*=q8_0
+blk\..*\.attn_v.*=q8_0
+blk\..*\.attn_output.*=iq5_ks
+
+# First 3 Dense Layers [0-2]
+blk\..*\.ffn_down\.weight=iq5_ks
+blk\..*\.ffn_(gate|up)\.weight=iq4_ks
+
+# Shared Expert Layers [3-92]
+blk\..*\.ffn_down_shexp\.weight=iq5_ks
+blk\..*\.ffn_(gate|up)_shexp\.weight=iq4_ks
+
+# Routed Experts Layers [3-92]
+blk\..*\.ffn_down_exps\.weight=iq4_kss
+blk\..*\.ffn_(gate|up)_exps\.weight=iq3_kt
+
+# NextN MTP Layer [92]
+blk\..*\.nextn\.embed_tokens\.weight=iq5_ks
+blk\..*\.nextn\.shared_head_head\.weight=iq5_ks
+blk\..*\.nextn\.eh_proj\.weight=q8_0
+
+# Non-Repeating Layers
+token_embd\.weight=iq4_k
+output\.weight=iq6_k
+"
+
+custom=$(
+  echo "$custom" | grep -v '^#' | \
+  sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
+)
+
+numactl -N 1 -m 1 \
+./build/bin/llama-quantize \
+    --custom-q "$custom" \
+    --imatrix /mnt/raid/models/ubergarm/GLM-4.6-GGUF/imatrix-GLM-4.6-BF16.dat \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-160x21B-4.5-BF16-00001-of-00015.gguf \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-4.6-IQ3_KT.gguf \
+    IQ3_KT \
+    192
+```
+
+</details>
+
+## IQ2_KL TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+#/usr/bin/env bash
+
+custom="
+# 93 Repeating Layers [0-92]
+
+# Attention
+blk\..*\.attn_q.*=iq5_ks
+blk\..*\.attn_k.*=iq5_ks
+blk\..*\.attn_v.*=iq5_ks
+blk\..*\.attn_output.*=iq5_ks
+
+# First 3 Dense Layers [0-2]
+blk\..*\.ffn_down\.weight=iq5_ks
+blk\..*\.ffn_(gate|up)\.weight=iq4_ks
+
+# Shared Expert Layers [3-92]
+blk\..*\.ffn_down_shexp\.weight=iq5_ks
+blk\..*\.ffn_(gate|up)_shexp\.weight=iq4_ks
+
+# Routed Experts Layers [3-92]
+blk\..*\.ffn_down_exps\.weight=iq3_k
+blk\..*\.ffn_(gate|up)_exps\.weight=iq2_kl
+
+# NextN MTP Layer [92]
+blk\..*\.nextn\.embed_tokens\.weight=iq5_ks
+blk\..*\.nextn\.shared_head_head\.weight=iq5_ks
+blk\..*\.nextn\.eh_proj\.weight=q8_0
+
+# Non-Repeating Layers
+token_embd\.weight=iq4_k
+output\.weight=iq6_k
+"
+
+custom=$(
+  echo "$custom" | grep -v '^#' | \
+  sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
+)
+
+numactl -N 1 -m 1 \
+./build/bin/llama-quantize \
+    --custom-q "$custom" \
+    --imatrix /mnt/raid/models/ubergarm/GLM-4.6-GGUF/imatrix-GLM-4.6-BF16.dat \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-160x21B-4.5-BF16-00001-of-00015.gguf \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-4.6-IQ2_KL.gguf \
+    IQ2_KL \
+    192
+```
+
+</details>
+
+## IQ2_KS TODO
+Final estimate: PPL = TODO
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+Used PR624 https://github.com/ikawrakow/ik_llama.cpp/pull/624
+
+```bash
+custom="
+#/usr/bin/env bash
+
+# 93 Repeating Layers [0-92]
+
+# Attention
+blk\..*\.attn_q.*=iq5_ks
+blk\..*\.attn_k.*=iq5_ks
+blk\..*\.attn_v.*=iq5_ks
+blk\..*\.attn_output.*=iq5_ks
+
+# First 3 Dense Layers [0-2]
+blk\..*\.ffn_down\.weight=iq5_ks
+blk\..*\.ffn_(gate|up)\.weight=iq4_ks
+
+# Shared Expert Layers [3-92]
+blk\..*\.ffn_down_shexp\.weight=iq5_ks
+blk\..*\.ffn_(gate|up)_shexp\.weight=iq4_ks
+
+# Routed Experts Layers [3-92]
+blk\..*\.ffn_down_exps\.weight=iq3_ks
+blk\..*\.ffn_(gate|up)_exps\.weight=iq2_ks
+
+# NextN MTP Layer [92]
+blk\..*\.nextn\.embed_tokens\.weight=iq5_ks
+blk\..*\.nextn\.shared_head_head\.weight=iq5_ks
+blk\..*\.nextn\.eh_proj\.weight=q8_0
+
+# Non-Repeating Layers
+token_embd\.weight=iq4_k
+output\.weight=iq6_k
+"
+
+custom=$(
+  echo "$custom" | grep -v '^#' | \
+  sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
+)
+
+numactl -N 1 -m 1 \
+./build/bin/llama-quantize \
+    --custom-q "$custom" \
+    --imatrix /mnt/raid/models/ubergarm/GLM-4.6-GGUF/imatrix-GLM-4.6-BF16.dat \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-160x21B-4.5-BF16-00001-of-00015.gguf \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-4.6-IQ2_KS.gguf \
+    IQ2_KS \
+    192
+```
+
+</details>
+
+## IQ1_KT TODO
+Final estimate: PPL = TODO
+
+*Good luck everybody!* 😅
+
+<details>
+
+<summary>👈 Secret Recipe</summary>
+
+```bash
+#/usr/bin/env bash
+
+custom="
+# 93 Repeating Layers [0-92]
+
+# Attention
+blk\..*\.attn_q.*=iq4_kt
+blk\..*\.attn_k.*=iq4_kt
+blk\..*\.attn_v.*=iq4_kt
+blk\..*\.attn_output.*=iq4_kt
+
+# First 3 Dense Layers [0-2]
+blk\..*\.ffn_down\.weight=iq4_kt
+blk\..*\.ffn_(gate|up)\.weight=iq4_kt
+
+# Shared Expert Layers [3-92]
+blk\..*\.ffn_down_shexp\.weight=iq4_kt
+blk\..*\.ffn_(gate|up)_shexp\.weight=iq4_kt
+
+# Routed Experts Layers [3-92]
+blk\..*\.ffn_down_exps\.weight=iq2_kt
+blk\..*\.ffn_(gate|up)_exps\.weight=iq1_kt
+
+# NextN MTP Layer [92]
+blk\..*\.nextn\.embed_tokens\.weight=iq4_kt
+blk\..*\.nextn\.shared_head_head\.weight=iq4_kt
+blk\..*\.nextn\.eh_proj\.weight=q8_0
+
+# Non-Repeating Layers
+token_embd\.weight=iq4_k
+output\.weight=iq6_k
+"
+
+custom=$(
+  echo "$custom" | grep -v '^#' | \
+  sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
+)
+
+numactl -N 0 -m 0 \
+./build/bin/llama-quantize \
+    --custom-q "$custom" \
+    --imatrix /mnt/raid/models/ubergarm/GLM-4.6-GGUF/imatrix-GLM-4.6-BF16.dat \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-160x21B-4.5-BF16-00001-of-00015.gguf \
+    /mnt/raid/models/ubergarm/GLM-4.6-GGUF/GLM-4.6-IQ1_KT.gguf \
+    IQ1_KT \
+    192
+```
+
+</details>
+
+
+## Quick Start
+If you want to disable thinking, add `/nothink` (correct, no underscore) at the *end* of your prompt. *TODO* confirm if this is still true for 4.6?
+
+```bash
+# Clone and checkout
+$ git clone https://github.com/ikawrakow/ik_llama.cpp
+$ cd ik_llama.cpp
+
+# Build for hybrid CPU+CUDA
+$ cmake -B build -DCMAKE_BUILD_TYPE=Release -DGGML_CUDA=ON -DGGML_BLAS=OFF -DGGML_SCHED_MAX_COPIES=1
+$ cmake --build build --config Release -j $(nproc)
+
+# Run API server
+$ ./build/bin/llama-server \
+    --model GLM-4.6-IQ4_KSS-00001-of-00004.gguf \
+    --alias ubergarm/GLM-4.6-IQ4_KSS \
+    --ctx-size 32768 \
+    -fa -fmoe \
+    -ctk q8_0 -ctv q8_0 \
+    -ub 4096 -b 4096 \
+    -ngl 99 \
+    -ot exps=CPU \
+    --parallel 1 \
+    --threads 8 \
+    --host 127.0.0.1 \
+    --port 8080 \
+    --no-mmap
+
+# MCP/Tool Use
+# --jinja etc...
+```
+
+## References
+* [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp)
+* [Getting Started Guide (already out of date lol)](https://github.com/ikawrakow/ik_llama.cpp/discussions/258)
+* [ubergarm-imatrix-calibration-corpus-v02.txt](https://gist.github.com/ubergarm/edfeb3ff9c6ec8b49e88cdf627b0711a?permalink_comment_id=5682584#gistcomment-5682584)