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/AMBEEPHA/forecast_next_30.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 639 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/AMBEEPHA/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/gru/models/AMBEEPHA/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/gru/resolve/main/models/AMBEEPHA/forecast_next_30.csv
639 Bytes
| step_ahead,prediction | |
| 1,704.0570176392794 | |
| 2,728.8685908854007 | |
| 3,696.1711591929197 | |
| 4,686.4216756761074 | |
| 5,712.4225750982762 | |
| 6,727.951174619794 | |
| 7,713.9895015895366 | |
| 8,729.4841270923615 | |
| 9,696.986182358861 | |
| 10,709.3995351195335 | |
| 11,671.5751472681761 | |
| 12,670.1513591468334 | |
| 13,690.2278844982386 | |
| 14,663.7116633921862 | |
| 15,675.4056148350239 | |
| 16,699.8234545230865 | |
| 17,683.9055374771357 | |
| 18,677.1690253823996 | |
| 19,680.3858409166336 | |
| 20,692.7722853124142 | |
| 21,704.120255240798 | |
| 22,694.2905765533447 | |
| 23,658.2263019442559 | |
| 24,675.0977878510952 | |
| 25,659.4046174764634 | |
| 26,655.8770309358836 | |
| 27,662.1820082247258 | |
| 28,662.9603488713503 | |
| 29,692.1528041154146 | |
| 30,643.820022648573 | |