Gemma 3 QAT
Collection
Quantization Aware Trained (QAT) Gemma 3 checkpoints. The model preserves similar quality as half precision while using 3x less memory.
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19 items
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Updated
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The Model mlx-community/gemma-3-1b-it-qat-bf16 was converted to MLX format from google/gemma-3-1b-it-qat-q4_0 using mlx-lm version 0.22.5.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/gemma-3-1b-it-qat-bf16")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)