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
Commit History
12 days ago
-
fix: Remediate 219 glitch tokens in tokenizer.json (#50)
- fix: Remediate 219 glitch tokens in tokenizer.json (2be4a76c1ccba0daf6baf271244aaba753840544) - Match upstream tokenizer.json formatting (68afa22021f7419b38f1b20ee288eab6dc9aff69) Co-authored-by: Gregory Kielian <gkielian@users.noreply.huggingface.co>4ecc2ba
-
Preparing for release!
Co-authored-by: Rocketknight1 <Rocketknight1@users.noreply.huggingface.co> Co-authored-by: RyanMullins <RyanMullins@users.noreply.huggingface.co> Co-authored-by: pcuenq <pcuenq@users.noreply.huggingface.co> Co-authored-by: bebechien <bebechien@users.noreply.huggingface.co> Co-authored-by: osanseviero <osanseviero@users.noreply.huggingface.co> Co-authored-by: douglas reid <douglas reid@users.noreply.huggingface.co>292a7e2