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)
Downloads last month
18
Safetensors
Model size
1.44B params
Tensor type
FP16
·
U32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for cyan2k/gemma-2-Ifable-9B-mlx-4bit

Quantized
(10)
this model

Dataset used to train cyan2k/gemma-2-Ifable-9B-mlx-4bit