Instructions to use keras/clip_vit_base_patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/clip_vit_base_patch32 with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/clip_vit_base_patch32") - Keras
How to use keras/clip_vit_base_patch32 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_base_patch32") - Notebooks
- Google Colab
- Kaggle
| { | |
| "keras_version": "3.11.3", | |
| "keras_hub_version": "0.23.0.dev0", | |
| "parameter_count": 151277363, | |
| "date_saved": "2025-09-15@12:04:24", | |
| "tasks": [] | |
| } |