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/ARAMIT/forecast_next_15.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 338 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ARAMIT/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/gru/models/ARAMIT/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/gru/resolve/main/models/ARAMIT/forecast_next_15.csv
338 Bytes
| step_ahead,prediction | |
| 1,164.07222835719585 | |
| 2,165.57386910915375 | |
| 3,164.29421401023865 | |
| 4,164.4546074271202 | |
| 5,164.41074660420418 | |
| 6,168.09712404757738 | |
| 7,164.46869070082903 | |
| 8,167.41363315284252 | |
| 9,167.24141186475754 | |
| 10,167.0321895033121 | |
| 11,167.17497622966766 | |
| 12,167.4742899686098 | |
| 13,162.45714189857244 | |
| 14,172.37356467545033 | |
| 15,170.792600274086 | |