Instructions to use zeromodels/gemma-3-27b-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/gemma-3-27b-pt 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-3-27b-pt") - Keras
How to use zeromodels/gemma-3-27b-pt with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/gemma-3-27b-pt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12b44b036cfa231cb536c7ae97da6ef29237a76869a1b4c45cb87a773be52a6b
- Size of remote file:
- 5.19 GB
- SHA256:
- 0f8df4ed9d7fb703715d70d78192086671f886f78e57b3a337898664411fd978
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.