Instructions to use danielle2035/intel-classifier-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use danielle2035/intel-classifier-models with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://danielle2035/intel-classifier-models") - Notebooks
- Google Colab
- Kaggle
Commit ·
8d95f09
0
Parent(s):
Add Intel Image Classifier models
Browse files- .gitattributes +2 -0
- README.md +8 -0
- model_best.keras +3 -0
- models/README.md +8 -0
- models/model_best.keras +3 -0
- models/pytorch_model.pth +3 -0
- pytorch_model.pth +3 -0
.gitattributes
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*.keras filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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README.md
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# Models folder
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Place your trained model files in this folder:
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- `pytorch_model.pth` (PyTorch model)
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- `model_best.keras` (TensorFlow model)
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If these files are not present, the app will not be able to classify images.
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model_best.keras
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version https://git-lfs.github.com/spec/v1
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oid sha256:1b57e8ec14d2c7fa3f168d95fdf02e98d6a5626ae5648975d98d0cb265aed8a9
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size 5157310
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models/README.md
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# Models folder
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Place your trained model files in this folder:
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- `pytorch_model.pth` (PyTorch model)
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- `model_best.keras` (TensorFlow model)
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If these files are not present, the app will not be able to classify images.
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models/model_best.keras
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:1b57e8ec14d2c7fa3f168d95fdf02e98d6a5626ae5648975d98d0cb265aed8a9
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size 5157310
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models/pytorch_model.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:13d195dc6d7c62d86cc3a039a39f7eef1a119f6e67c1960fd161219635ac31c2
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size 4859453
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pytorch_model.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:13d195dc6d7c62d86cc3a039a39f7eef1a119f6e67c1960fd161219635ac31c2
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size 4859453
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