Instructions to use ramirces/anomalydetectiondataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ramirces/anomalydetectiondataset 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://ramirces/anomalydetectiondataset") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from ramirces/anomalydetectiondataset: direct link, hf CLI and curl.
- Browser
- Download file 338 kB
-
https://huggingface.co/ramirces/anomalydetectiondataset/resolve/refs%2Fpr%2F1/saved_model.pb
- Command line
-
hf download hf://ramirces/anomalydetectiondataset@refs/pr/1/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/ramirces/anomalydetectiondataset/resolve/refs%2Fpr%2F1/saved_model.pb
338 kB
- Xet hash:
- 0f7411be449d65e4627bc69626a75396be5ee6dedcb789f32b5e2eb13e00c528
- Size of remote file:
- 338 kB
- SHA256:
- 12b8349fe5937e7473646bb01b62660361a49d84d5b20526e4729c15ec25b824
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