Instructions to use StockCast/gru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use StockCast/gru 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/gru") - Notebooks
- Google Colab
- Kaggle
Download models/ACMEPL/scaler_ACMEPL.bin from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 959 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ACMEPL/scaler_ACMEPL.bin
- Command line
-
hf download hf://StockCast/gru/models/ACMEPL/scaler_ACMEPL.bin
-
curl -L -o scaler_ACMEPL.bin https://huggingface.co/StockCast/gru/resolve/main/models/ACMEPL/scaler_ACMEPL.bin
959 Bytes
- Xet hash:
- aa7aa0f1fa50b944a06f80260e0ad29f15705c1a40cd405bd1eb9ef1a7d58cfc
- Size of remote file:
- 959 Bytes
- SHA256:
- f698a485ae19583636c8d2985d417167aaf8f80512f81384c208212e9d85df9d
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