Instructions to use keras/siglip_large_patch16_256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/siglip_large_patch16_256 with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/siglip_large_patch16_256") - Keras
How to use keras/siglip_large_patch16_256 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras/siglip_large_patch16_256") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0943d040ec10dc6bb383cada68fc2569fe6276d46c733e4b3c581e7dded00e0f
- Size of remote file:
- 2.61 GB
- SHA256:
- e13d6fa8d032daf4a3c48b9f812c88be35aec8c49ecafe6f1f7351c0060b6752
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