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/00DSES/forecast_next_7.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 168 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/00DSES/forecast_next_7.csv
- Command line
-
hf download hf://StockCast/gru/models/00DSES/forecast_next_7.csv
-
curl -L -o forecast_next_7.csv https://huggingface.co/StockCast/gru/resolve/main/models/00DSES/forecast_next_7.csv
168 Bytes
| step_ahead,prediction | |
| 1,1171.5162611029589 | |
| 2,1176.3360795031142 | |
| 3,1174.0368736251903 | |
| 4,1177.0108205527263 | |
| 5,1176.6280239486264 | |
| 6,1177.6305738792603 | |
| 7,1174.292358100286 | |