cyan2k/gemma-2-Ifable-9B-mlx-4bit

The Model cyan2k/gemma-2-Ifable-9B-mlx-4bit was converted to MLX format from ifable/gemma-2-Ifable-9B using mlx-lm version 0.18.2.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("cyan2k/gemma-2-Ifable-9B-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)
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FP16
·
U32
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Dataset used to train cyan2k/gemma-2-Ifable-9B-mlx-4bit