Instructions to use Ellbendls/ToxicityDetect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Ellbendls/ToxicityDetect with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Ellbendls/ToxicityDetect") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 424f15910f4e82ba48be93a2163b619383056cc543e41057df5159b007afbd79
- Size of remote file:
- 77.6 MB
- SHA256:
- 165dd163b69f9ba71c6a78193a3d2f3a196ff8d0916d4194e8f848f9ae423c7b
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