Instructions to use joycerlz/distilbert-binary-polar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use joycerlz/distilbert-binary-polar 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://joycerlz/distilbert-binary-polar") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from joycerlz/distilbert-binary-polar: direct link, hf CLI and curl.
- Browser
- Download file 3.16 MB
-
https://huggingface.co/joycerlz/distilbert-binary-polar/resolve/main/saved_model.pb
- Command line
-
hf download hf://joycerlz/distilbert-binary-polar/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/joycerlz/distilbert-binary-polar/resolve/main/saved_model.pb
3.16 MB
- Xet hash:
- a2eb1da6e13bf7c8fbd74cfd3a3333a2871d171d0b59b6a749dd774db57f3352
- Size of remote file:
- 3.16 MB
- SHA256:
- 7cf2e96d743ce74385c5764896a0744163ed8a0d7e71fcef5d5fe17f4877d948
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