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_15.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 337 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ACMEPL/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/gru/models/ACMEPL/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/gru/resolve/main/models/ACMEPL/forecast_next_15.csv
337 Bytes
| step_ahead,prediction | |
| 1,12.129521518945694 | |
| 2,15.542775613069534 | |
| 3,16.919414651393893 | |
| 4,17.057623553276063 | |
| 5,14.160476335883141 | |
| 6,14.467724826931953 | |
| 7,16.33818382024765 | |
| 8,17.302512598037723 | |
| 9,17.87607231140137 | |
| 10,17.731322968006136 | |
| 11,15.236238676309585 | |
| 12,18.15686172246933 | |
| 13,13.161562439799308 | |
| 14,16.542323189973832 | |
| 15,16.730197930336 | |