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/ACFL/scaler_ACFL.bin from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 719 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/ACFL/scaler_ACFL.bin
- Command line
-
hf download hf://StockCast/seperate/models/ACFL/scaler_ACFL.bin
-
curl -L -o scaler_ACFL.bin https://huggingface.co/StockCast/seperate/resolve/main/models/ACFL/scaler_ACFL.bin
719 Bytes
- Xet hash:
- f65b62f3f9eefeca513ffe025361863add61fff058dc38d60b1b9e1c40c0e367
- Size of remote file:
- 719 Bytes
- SHA256:
- e196678327fe74162cfc490dce86c136f0b4a79efbed3eb9496c9a75f2f8952e
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