from mlx_lm import load, generate

model, tokenizer = load("salohcin714/gemma-4-E4B-it-nvfp4-mlx")
messages = [{"role": "user", "content": "Hello"}]
prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
text = generate(model, tokenizer, prompt=prompt, verbose=True)

Modifications

Weights converted to MLX safetensors layout and quantized (NVFP4 (Nvidia-style) microscaling floating-point quantization, via round-to-nearest, no calibration). No fine-tuning; no added training data.

License and attribution

Licensed under Apache 2.0. Original weights by Google. See the upstream model card and the included LICENSE file for the full text.

Disclaimer

This repository is not affiliated with or endorsed by Google. "Gemma" is a Google trademark, used here descriptively to identify the origin of the base model.