Instructions to use kerasformers/gemma-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/gemma-7b with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use kerasformers/gemma-7b with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kerasformers/gemma-7b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0e6dadb8e68f844cab4c8baf46484a596d09e6216bfa6fe0351e29bb30941a7
- Size of remote file:
- 17.5 MB
- SHA256:
- c15eb04bc5ad609fb26533e8525302c5640a945e5f67f65b7c849900acda7d99
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.