Instructions to use keras/dinov2_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/dinov2_small with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/dinov2_small") - Keras
How to use keras/dinov2_small 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/dinov2_small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 792057546d2b6aa8cf96d34256664c531bcebb6f057e04a65d539e9a9711f727
- Size of remote file:
- 90.9 MB
- SHA256:
- 6dba391a5fe3473edc5bc23c74ebf34fc6beed81614c5a2cbe0a1dcf365e50cb
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