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_15.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 334 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ALLTEX/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/gru/models/ALLTEX/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/gru/resolve/main/models/ALLTEX/forecast_next_15.csv
334 Bytes
| step_ahead,prediction | |
| 1,12.873145230580121 | |
| 2,12.657423304487018 | |
| 3,12.499150880984962 | |
| 4,12.50336081124842 | |
| 5,12.800557270087301 | |
| 6,13.06346470415592 | |
| 7,12.63564171437174 | |
| 8,12.63048737058416 | |
| 9,12.679474517703056 | |
| 10,12.555320406518875 | |
| 11,12.6679041698575 | |
| 12,12.54257924966514 | |
| 13,12.683924764208495 | |
| 14,12.4412053598091 | |
| 15,12.598726795054972 | |