Instructions to use kerasformers/owlvit-large-patch14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/owlvit-large-patch14 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-large-patch14 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-large-patch14") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a6c269cd873462d19d4d25989e8f4be0a0e4b784da6bef6e3e5a68e66a222eb
- Size of remote file:
- 1.73 GB
- SHA256:
- 6fac680f25b51c8263d0fee65b13805e0f8817ed0c0bc5b9209bb19f1d2e2c6f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.