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_30.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 658 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ACMEPL/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/gru/models/ACMEPL/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/gru/resolve/main/models/ACMEPL/forecast_next_30.csv
658 Bytes
| step_ahead,prediction | |
| 1,19.099732756614685 | |
| 2,16.204964864254 | |
| 3,15.35739607810974 | |
| 4,17.032370698452 | |
| 5,14.51577868461609 | |
| 6,13.525781010091304 | |
| 7,12.649026003479957 | |
| 8,13.721914115548135 | |
| 9,17.8474892616272 | |
| 10,14.33794520497322 | |
| 11,16.073824548721316 | |
| 12,17.521279859542847 | |
| 13,13.77492153942585 | |
| 14,13.669492253661156 | |
| 15,13.601669983565808 | |
| 16,16.999239838123323 | |
| 17,13.245320934057236 | |
| 18,15.186385941505431 | |
| 19,20.47991887331009 | |
| 20,13.771280896663665 | |
| 21,15.574269735813141 | |
| 22,15.07754277586937 | |
| 23,15.308090782165527 | |
| 24,15.081511533260345 | |
| 25,12.418925188481808 | |
| 26,16.38866465687752 | |
| 27,22.013901138305666 | |
| 28,11.245614299178124 | |
| 29,14.752472883462906 | |
| 30,15.859796643257143 | |