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/1STPRIMFMF/forecast_next_15.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 336 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/1STPRIMFMF/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/gru/models/1STPRIMFMF/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/gru/resolve/main/models/1STPRIMFMF/forecast_next_15.csv
336 Bytes
| step_ahead,prediction | |
| 1,20.658224016427994 | |
| 2,20.611929088830948 | |
| 3,20.38343036174774 | |
| 4,20.500217765569687 | |
| 5,20.442723274230957 | |
| 6,20.34153425693512 | |
| 7,20.459759324789047 | |
| 8,20.354882270097733 | |
| 9,20.21647357940674 | |
| 10,20.138896048069 | |
| 11,20.115534007549286 | |
| 12,20.052362620830536 | |
| 13,19.997641533613205 | |
| 14,19.946643352508545 | |
| 15,19.98468244075775 | |