Instructions to use KerasFormers/owlvit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use KerasFormers/owlvit-base-patch32 with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use KerasFormers/owlvit-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://KerasFormers/owlvit-base-patch32") - Notebooks
- Google Colab
- Kaggle
owlvit-base-patch32 (Keras 3)
Pure-Keras 3 weights for kerasformers, mirrored from the GitHub release. Apache 2.0.
from kerasformers.models.owlvit import OwlViTDetect
model = OwlViTDetect.from_weights("owlvit-base-patch32")
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