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/ABB1STMF/forecast_next_7.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 167 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ABB1STMF/forecast_next_7.csv
- Command line
-
hf download hf://StockCast/gru/models/ABB1STMF/forecast_next_7.csv
-
curl -L -o forecast_next_7.csv https://huggingface.co/StockCast/gru/resolve/main/models/ABB1STMF/forecast_next_7.csv
167 Bytes
| step_ahead,prediction | |
| 1,3.3308910146355633 | |
| 2,3.3767583534121517 | |
| 3,3.407292062044144 | |
| 4,3.3664552062749866 | |
| 5,3.408976992219687 | |
| 6,3.4193610526621345 | |
| 7,3.4042859204113487 | |