Instructions to use keras/clip_vit_large_patch14_336 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/clip_vit_large_patch14_336 with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/clip_vit_large_patch14_336") - Keras
How to use keras/clip_vit_large_patch14_336 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/clip_vit_large_patch14_336") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f609d8d1a585568c0b3dc1fc49a4dcbf5e96cf2c65fe2e6678459f1e1f763563
- Size of remote file:
- 1.71 GB
- SHA256:
- dc5f72e0a660961f0f379ab38de5f879576e1cc42f1443c5c3a288bcf66e4b38
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