library_name: transformers license: apache-2.0 language:

• en tags:
• 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
• moe
• mixture of experts
• not-for-all-audiences
• mlx
• mlx-my-repo base_model: DavidAU/L3.1-MOE-6X8B-Dark-Reasoning-Dantes-Peak-Hermes-R1-Uncensored-36B pipeline_tag: text-generation

insmek/L3.1-MOE-6X8B-Dark-Reasoning-Dantes-Peak-Hermes-R1-Uncensored-36B-mlx-8Bit

The Model insmek/L3.1-MOE-6X8B-Dark-Reasoning-Dantes-Peak-Hermes-R1-Uncensored-36B-mlx-8Bit 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("insmek/L3.1-MOE-6X8B-Dark-Reasoning-Dantes-Peak-Hermes-R1-Uncensored-36B-mlx-8Bit")

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)