thliang01/gemma-3-4B-T1-it-mlx-fp16
The Model thliang01/gemma-3-4B-T1-it-mlx-fp16 was converted to MLX format from twinkle-ai/gemma-3-4B-T1-it using mlx-lm version 0.29.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("thliang01/gemma-3-4B-T1-it-mlx-fp16")
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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Model size
5B params
Tensor type
F16
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Datasets used to train thliang01/gemma-3-4B-T1-it-mlx-fp16
Evaluation results
- single choice on tmmlu+test set self-reported47.440
- single choice on mmlutest set self-reported59.130
- single choice on tw-legal-benchmark-v1test set self-reported44.180