Instructions to use emmachen/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use emmachen/test 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://emmachen/test") - Notebooks
- Google Colab
- Kaggle
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Download README.md from emmachen/test: direct link, hf CLI and curl.
- Browser
- Download file 198 Bytes
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https://huggingface.co/emmachen/test/resolve/main/README.md
- Command line
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hf download hf://emmachen/test/README.md
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curl -L -o README.md https://huggingface.co/emmachen/test/resolve/main/README.md
198 Bytes
metadata
datasets:
- gsdf/EasyNegative
metrics:
- accuracy
library_name: keras
pipeline_tag: text-classification
tags:
- legal