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/1STPRIMFMF/forecast_next_30.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 662 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/1STPRIMFMF/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/gru/models/1STPRIMFMF/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/gru/resolve/main/models/1STPRIMFMF/forecast_next_30.csv
662 Bytes
| step_ahead,prediction | |
| 1,20.676015108823776 | |
| 2,20.225603818893433 | |
| 3,20.26919776201248 | |
| 4,20.478391289711 | |
| 5,20.412872970104218 | |
| 6,20.08433187007904 | |
| 7,19.954947471618652 | |
| 8,20.376397609710693 | |
| 9,20.374305486679077 | |
| 10,20.103026866912842 | |
| 11,20.05889916419983 | |
| 12,19.922039449214935 | |
| 13,19.917774736881256 | |
| 14,19.964956134557724 | |
| 15,20.081814616918564 | |
| 16,19.851170122623444 | |
| 17,19.87184190750122 | |
| 18,19.808527022600174 | |
| 19,19.575913786888123 | |
| 20,19.674321353435516 | |
| 21,19.892206579446793 | |
| 22,19.80485239624977 | |
| 23,19.45578971505165 | |
| 24,19.445656329393387 | |
| 25,19.538494288921356 | |
| 26,19.51890879869461 | |
| 27,19.338717997074127 | |
| 28,19.33500850200653 | |
| 29,19.479676127433777 | |
| 30,19.297183990478516 | |