license: apache-2.0
language:

• en
  library_name: transformers
  pipeline_tag: text-generation
  base_model: huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated
  tags:
• text-generation
• reasoning
• distillation
• chain-of-thought
• qwen
• qwen3.6
• mixture-of-experts
• moe
• lora
• unsloth
• abliterated
• uncensored
• mlx
• mlx-my-repo

vectoronfire/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-mlx-4Bit

The Model vectoronfire/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-mlx-4Bit was converted to MLX format from huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated using mlx-lm version 0.31.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("vectoronfire/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-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)