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:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://danielle2035/intel-classifier-models") - Notebooks
- Google Colab
- Kaggle
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Download README.md from danielle2035/intel-classifier-models: direct link, hf CLI and curl.
- Browser
- Download file 221 Bytes
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https://huggingface.co/danielle2035/intel-classifier-models/resolve/main/README.md
- Command line
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hf download hf://danielle2035/intel-classifier-models/README.md
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curl -L -o README.md https://huggingface.co/danielle2035/intel-classifier-models/resolve/main/README.md
221 Bytes
| # Models folder | |
| Place your trained model files in this folder: | |
| - `pytorch_model.pth` (PyTorch model) | |
| - `model_best.keras` (TensorFlow model) | |
| If these files are not present, the app will not be able to classify images. | |