Instructions to use kerasformers/deit_base_patch16_224_fb_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/deit_base_patch16_224_fb_in1k 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/deit_base_patch16_224_fb_in1k 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/deit_base_patch16_224_fb_in1k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c731d2b708b3094d521eccceb13fa055328e5fd10677a07a1defdc0b40a09851
- Size of remote file:
- 347 MB
- SHA256:
- 8a8d0bba51e43407b0ecf521c74908a912bbc4aae6aab3aa12e2b8c98cf88c35
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.