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/APOLOISPAT/forecast_next_15.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 325 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/APOLOISPAT/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/gru/models/APOLOISPAT/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/gru/resolve/main/models/APOLOISPAT/forecast_next_15.csv
325 Bytes
| step_ahead,prediction | |
| 1,4.705814725071166 | |
| 2,4.529782580450795 | |
| 3,4.896136333953198 | |
| 4,4.724613787688887 | |
| 5,4.753467132385231 | |
| 6,4.5664167508575 | |
| 7,4.875593212740093 | |
| 8,4.550227945760906 | |
| 9,4.308752013827096 | |
| 10,4.73750940436351 | |
| 11,4.66216933805124 | |
| 12,4.8941882123396345 | |
| 13,4.439606744025333 | |
| 14,4.675223346497117 | |
| 15,4.757512244442766 | |