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/ARAMITCEM/forecast_next_7.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 169 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ARAMITCEM/forecast_next_7.csv
- Command line
-
hf download hf://StockCast/gru/models/ARAMITCEM/forecast_next_7.csv
-
curl -L -o forecast_next_7.csv https://huggingface.co/StockCast/gru/resolve/main/models/ARAMITCEM/forecast_next_7.csv
169 Bytes
| step_ahead,prediction | |
| 1,14.660468409872054 | |
| 2,14.320551241779327 | |
| 3,14.570426625686883 | |
| 4,14.730119072812794 | |
| 5,14.968194642549753 | |
| 6,14.653743302991986 | |
| 7,14.532189201644062 | |