metadata
language:
- en
- zh
library_name: transformers
license: mit
pipeline_tag: text-generation
base_model: huihui-ai/Huihui-Qwen3-Next-80B-A3B-Instruct-abliterated-mlx-4bit
tags:
- abliterated
- uncensored
- mlx
- chat
- mlx
- mlx-my-repo
introvoyz041/Huihui-Qwen3-Next-80B-A3B-Instruct-abliterated-mlx-4bit-mlx-4Bit
The Model introvoyz041/Huihui-Qwen3-Next-80B-A3B-Instruct-abliterated-mlx-4bit-mlx-4Bit was converted to MLX format from huihui-ai/Huihui-Qwen3-Next-80B-A3B-Instruct-abliterated-mlx-4bit using mlx-lm version 0.28.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("introvoyz041/Huihui-Qwen3-Next-80B-A3B-Instruct-abliterated-mlx-4bit-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)