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/AMCL(PRAN)/forecast_next_15.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 340 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/AMCL(PRAN)/forecast_next_15.csv
- Command line
-
hf download 'hf://StockCast/gru/models/AMCL(PRAN)/forecast_next_15.csv'
-
curl -L -o forecast_next_15.csv 'https://huggingface.co/StockCast/gru/resolve/main/models/AMCL(PRAN)/forecast_next_15.csv'
340 Bytes
| step_ahead,prediction | |
| 1,203.74281320273877 | |
| 2,204.01307879686357 | |
| 3,204.72655622065068 | |
| 4,203.2361182153225 | |
| 5,203.36149024367333 | |
| 6,203.50867347717286 | |
| 7,203.61245478689673 | |
| 8,203.75276901721955 | |
| 9,203.80702566206458 | |
| 10,203.8353836208582 | |
| 11,203.07875868082047 | |
| 12,204.00034146010879 | |
| 13,202.70866357386114 | |
| 14,204.90396306812764 | |
| 15,203.8214420884848 | |