Instructions to use zeromodels/deit3_small_patch16_224_fb_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use zeromodels/deit3_small_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://zeromodels/deit3_small_patch16_224_fb_in1k") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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---
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pipeline_tag: image-classification
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license: apache-2.0
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base_model: timm/deit3_small_patch16_224.fb_in1k
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library_name: kerasformers
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tags:
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```
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---
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pipeline_tag: image-classification
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license: apache-2.0
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base_model: timm/deit3_small_patch16_224.fb_in1k
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library_name: kerasformers
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tags:
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- keras
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- kerasformers
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- image-classification
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- deit
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- tensorflow
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- jax
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- pytorch
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---
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# deit3_small_patch16_224_fb_in1k
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Pure-Keras 3 image-classification weight for [kerasformers](https://github.com/IMvision12/KerasFormers), converted from [timm/deit3_small_patch16_224.fb_in1k](https://huggingface.co/timm/deit3_small_patch16_224.fb_in1k).
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## Usage
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```python
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from kerasformers.models.deit import DeiTImageClassify
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model = DeiTImageClassify.from_weights("deit3_small_patch16_224_fb_in1k")
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```
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License: **apache-2.0**, inherited from the upstream source.
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