Instructions to use zeromodels/gemma-4-e4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/gemma-4-e4b with ZeroModels:
# pip install -U zeromodels # ZeroModels is pure Keras 3, so pick a backend: "jax", "torch" or "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" from zeromodels import AutoZModel # AutoZModel reads the repo's model_type and loads the matching class. # For a task head use the matching loader, e.g. AutoZMImageClassify / AutoZMDetect / # AutoZMSemanticSegment / AutoZMTextGenerate (see zeromodels.auto). model = AutoZModel.from_weights("zeromodels/gemma-4-e4b") - Keras
How to use zeromodels/gemma-4-e4b with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://zeromodels/gemma-4-e4b") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from zeromodels/gemma-4-e4b: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/zeromodels/gemma-4-e4b/resolve/main/tokenizer.json
- Command line
-
hf download hf://zeromodels/gemma-4-e4b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/zeromodels/gemma-4-e4b/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- 2e7ad99fe28ec40cd28867fbe6c65c1ec92ce18051c4fdb8eccad32e16989ada
- Size of remote file:
- 32.2 MB
- SHA256:
- 12bac982b793c44b03d52a250a9f0d0b666813da566b910c24a6da0695fd11e6
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