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/ALIF/forecast_next_15.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 327 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ALIF/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/gru/models/ALIF/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/gru/resolve/main/models/ALIF/forecast_next_15.csv
327 Bytes
| step_ahead,prediction | |
| 1,8.552869672944206 | |
| 2,6.781191480657996 | |
| 3,7.992873447012145 | |
| 4,7.280323540829842 | |
| 5,7.804599684069503 | |
| 6,8.598894243015852 | |
| 7,8.308000463177887 | |
| 8,9.077900586073438 | |
| 9,8.088958044628363 | |
| 10,8.444233354521879 | |
| 11,8.715348748004722 | |
| 12,9.63003217806114 | |
| 13,9.368778655768907 | |
| 14,8.962526665668554 | |
| 15,8.849775656011134 | |