Text Generation
Transformers
Safetensors
MLX
English
mixtral
creative
creative writing
fiction writing
plot generation
sub-plot generation
story generation
scene continue
storytelling
fiction story
science fiction
romance
all genres
llama 3.1
llama-3
llama3
llama-3.1
story
writing
vivid prosing
vivid writing
fiction
roleplaying
bfloat16
swearing
role play
sillytavern
backyard
horror
context 128k
mergekit
Merge
6X8B
Mixture of Experts
mixture of experts
Not-For-All-Audiences
mlx-my-repo
conversational
text-generation-inference
4-bit precision
hsefz-ChenJunJie/L3.1-MOE-6X8B-Dark-Reasoning-Dantes-Peak-Hermes-R1-Uncensored-36B-mlx-4Bit
The Model hsefz-ChenJunJie/L3.1-MOE-6X8B-Dark-Reasoning-Dantes-Peak-Hermes-R1-Uncensored-36B-mlx-4Bit was converted to MLX format from DavidAU/L3.1-MOE-6X8B-Dark-Reasoning-Dantes-Peak-Hermes-R1-Uncensored-36B using mlx-lm version 0.22.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("hsefz-ChenJunJie/L3.1-MOE-6X8B-Dark-Reasoning-Dantes-Peak-Hermes-R1-Uncensored-36B-mlx-4Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
- Downloads last month
- 95