Instructions to use kerasformers/deit_base_patch16_384_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_384_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_384_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_384_fb_in1k") - Notebooks
- Google Colab
- Kaggle
| pipeline_tag: image-classification | |
| license: apache-2.0 | |
| base_model: timm/deit_base_patch16_384.fb_in1k | |
| library_name: kerasformers | |
| tags: | |
| - keras | |
| - kerasformers | |
| - image-classification | |
| - deit | |
| - tf | |
| - jax | |
| - pytorch | |
| # deit_base_patch16_384_fb_in1k | |
| Pure-Keras 3 image-classification weight for [kerasformers](https://github.com/IMvision12/KerasFormers), converted from [timm/deit_base_patch16_384.fb_in1k](https://huggingface.co/timm/deit_base_patch16_384.fb_in1k). | |
| ## Usage | |
| ```python | |
| from kerasformers.models.deit import DeiTImageClassify | |
| model = DeiTImageClassify.from_weights("deit_base_patch16_384_fb_in1k") | |
| ``` | |
| License: **apache-2.0**, inherited from the upstream source. | |