Instructions to use septa/bird-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use septa/bird-classification 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://septa/bird-classification") - Notebooks
- Google Colab
- Kaggle
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Download README.md from septa/bird-classification: direct link, hf CLI and curl.
- Browser
- Download file 63 Bytes
-
https://huggingface.co/septa/bird-classification/resolve/main/README.md
- Command line
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hf download hf://septa/bird-classification/README.md
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curl -L -o README.md https://huggingface.co/septa/bird-classification/resolve/main/README.md
63 Bytes
metadata
tags:
- biology
metrics:
- accuracy
library_name: keras