Instructions to use StockCast/seperate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use StockCast/seperate 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://StockCast/seperate") - Notebooks
- Google Colab
- Kaggle
Download models/AMBEEPHA/scaler_AMBEEPHA.bin from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 719 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/AMBEEPHA/scaler_AMBEEPHA.bin
- Command line
-
hf download hf://StockCast/seperate/models/AMBEEPHA/scaler_AMBEEPHA.bin
-
curl -L -o scaler_AMBEEPHA.bin https://huggingface.co/StockCast/seperate/resolve/main/models/AMBEEPHA/scaler_AMBEEPHA.bin
719 Bytes
- Xet hash:
- e76413e1495368d3021dec7bef7bfd84912abe79a4ae408b1595824abc91ce60
- Size of remote file:
- 719 Bytes
- SHA256:
- 887b1e163597d1409474514f19212f742e1c30eedeb2ead9b1b2a00344ef87ae
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