library_name: mlx
license: apache-2.0
pipeline_tag: text-generation
base_model: huihui-ai/Huihui-OmniCoder-9B-abliterated
tags:
- abliterated
- uncensored
- qwen3.5
- code
- agent
- sft
- omnicoder
- tesslate
- mlx
piotreknow02/Huihui-OmniCoder-9B-abliterated-mlx-4bit
This model piotreknow02/Huihui-OmniCoder-9B-abliterated-mlx-4bit was
converted to MLX format from huihui-ai/Huihui-OmniCoder-9B-abliterated
using mlx-lm version 0.31.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("piotreknow02/Huihui-OmniCoder-9B-abliterated-mlx-4bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False,
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)