Instructions to use google/gemma-4-E4B-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-4-E4B-it with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("google/gemma-4-E4B-it") model = AutoModelForMultimodalLM.from_pretrained("google/gemma-4-E4B-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- AMD Developer Cloud
Download tokenizer.json from google/gemma-4-E4B-it: direct link, hf CLI and curl.
- Browser
- Download file 15.1 MB
-
https://huggingface.co/google/gemma-4-E4B-it/resolve/2be4a76c1ccba0daf6baf271244aaba753840544/tokenizer.json
- Command line
-
hf download hf://google/gemma-4-E4B-it@2be4a76c1ccba0daf6baf271244aaba753840544/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/google/gemma-4-E4B-it/resolve/2be4a76c1ccba0daf6baf271244aaba753840544/tokenizer.json
15.1 MB
- Xet hash:
- 847b26e7fcf51bd5f2a1de741719e6cb50cc2d71310cb0afa1a4a3add57daa65
- Size of remote file:
- 15.1 MB
- SHA256:
- 6674dbb0510f80ba5033b93dd0a0f3573fed19626785f03f4fdc0466616f592c
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