Instructions to use OsGo/gemma-4-E2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OsGo/gemma-4-E2B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("OsGo/gemma-4-E2B") model = AutoModelForMultimodalLM.from_pretrained("OsGo/gemma-4-E2B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from OsGo/gemma-4-E2B: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/OsGo/gemma-4-E2B/resolve/main/tokenizer.json
- Command line
-
hf download hf://OsGo/gemma-4-E2B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/OsGo/gemma-4-E2B/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- 2e7ad99fe28ec40cd28867fbe6c65c1ec92ce18051c4fdb8eccad32e16989ada
- Size of remote file:
- 32.2 MB
- SHA256:
- 12bac982b793c44b03d52a250a9f0d0b666813da566b910c24a6da0695fd11e6
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