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/ARAMIT/forecast_next_7.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 164 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ARAMIT/forecast_next_7.csv
- Command line
-
hf download hf://StockCast/gru/models/ARAMIT/forecast_next_7.csv
-
curl -L -o forecast_next_7.csv https://huggingface.co/StockCast/gru/resolve/main/models/ARAMIT/forecast_next_7.csv
164 Bytes
| step_ahead,prediction | |
| 1,166.9046085551381 | |
| 2,165.9340371415019 | |
| 3,164.67924343794584 | |
| 4,165.88995805382729 | |
| 5,166.4052083939314 | |
| 6,165.2994063720107 | |
| 7,164.7944144755602 | |