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/ALLTEX/forecast_next_30.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 671 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ALLTEX/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/gru/models/ALLTEX/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/gru/resolve/main/models/ALLTEX/forecast_next_30.csv
671 Bytes
| step_ahead,prediction | |
| 1,12.815889885928481 | |
| 2,12.818126731924712 | |
| 3,12.920080897584556 | |
| 4,12.973149757459758 | |
| 5,12.93199853170663 | |
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| 21,12.824613072443753 | |
| 22,12.777408515010029 | |
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| 24,12.677304344810544 | |
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| 27,13.018991545960306 | |
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| 30,12.736394298821686 | |