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/ACFL/forecast_next_30.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 661 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ACFL/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/gru/models/ACFL/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/gru/resolve/main/models/ACFL/forecast_next_30.csv
661 Bytes
| step_ahead,prediction | |
| 1,19.743102033436298 | |
| 2,21.281158746033906 | |
| 3,20.60669510513544 | |
| 4,20.908222579210996 | |
| 5,20.887332063913345 | |
| 6,18.84502964913845 | |
| 7,18.397490110993385 | |
| 8,20.04613536298275 | |
| 9,20.076297771930694 | |
| 10,19.990513202548026 | |
| 11,19.25255625396967 | |
| 12,20.444465455412864 | |
| 13,19.48671908006072 | |
| 14,22.03429917693138 | |
| 15,21.571912363916635 | |
| 16,22.354842898249625 | |
| 17,18.562292632460593 | |
| 18,21.282594528794288 | |
| 19,20.98002516552806 | |
| 20,22.389283281564712 | |
| 21,22.48749832510948 | |
| 22,21.42072624415159 | |
| 23,20.85490609407425 | |
| 24,20.587443158775567 | |
| 25,22.39533360004425 | |
| 26,21.180914779007434 | |
| 27,23.655189265310764 | |
| 28,21.017644655704498 | |
| 29,23.283912193775176 | |
| 30,22.78477932214737 | |