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/ACMEPL/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/ACMEPL/forecast_next_7.csv
- Command line
-
hf download hf://StockCast/gru/models/ACMEPL/forecast_next_7.csv
-
curl -L -o forecast_next_7.csv https://huggingface.co/StockCast/gru/resolve/main/models/ACMEPL/forecast_next_7.csv
169 Bytes
| step_ahead,prediction | |
| 1,17.074167132377625 | |
| 2,15.072236454486847 | |
| 3,18.507849299907686 | |
| 4,16.333934950828553 | |
| 5,15.194348561763762 | |
| 6,14.292695489525794 | |
| 7,18.545050501823425 | |