openbmb/UltraData-Math
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How to use nhe-ai/Crow-9B-HERETIC-4.6-mlx-4Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Crow-9B-HERETIC-4.6-mlx-4Bit nhe-ai/Crow-9B-HERETIC-4.6-mlx-4Bit
The Model nhe-ai/Crow-9B-HERETIC-4.6-mlx-4Bit was converted to MLX format from Crownelius/Crow-9B-HERETIC-4.6 using mlx-lm version 0.31.2.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("nhe-ai/Crow-9B-HERETIC-4.6-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)
4-bit
Base model
Qwen/Qwen3.5-9B-Base