Text Generation
ZeroModels
Keras
PyTorch
JAX
TensorFlow
English
gemma2
gemma
gemma-2-9b
arxiv:2408.00118
Instructions to use zeromodels/gemma-2-9b-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/gemma-2-9b-it 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-2-9b-it") - Keras
How to use zeromodels/gemma-2-9b-it 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-2-9b-it") - Notebooks
- Google Colab
- Kaggle
Download model_00002.weights.h5 from zeromodels/gemma-2-9b-it: direct link, hf CLI and curl.
- Browser
- Download file 5.36 GB
-
https://huggingface.co/zeromodels/gemma-2-9b-it/resolve/main/model_00002.weights.h5
- Command line
-
hf download hf://zeromodels/gemma-2-9b-it/model_00002.weights.h5
-
curl -L -o model_00002.weights.h5 https://huggingface.co/zeromodels/gemma-2-9b-it/resolve/main/model_00002.weights.h5
5.36 GB
- Xet hash:
- 155341702370e45f634c448507c193377d5e905db57c96a608afeb045393d2b1
- Size of remote file:
- 5.36 GB
- SHA256:
- b1a81cbf9911497781f9769dd64e12a61ea0bd9ba7bfbb98d15dbc629c6e7869
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