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_30.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 639 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/ALIF/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/gru/models/ALIF/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/gru/resolve/main/models/ALIF/forecast_next_30.csv
639 Bytes
| step_ahead,prediction | |
| 1,7.083601136471724 | |
| 2,6.80334039090611 | |
| 3,5.775055895873203 | |
| 4,6.4954728266737245 | |
| 5,7.241277006225939 | |
| 6,6.78327648978733 | |
| 7,6.861047501073931 | |
| 8,7.68773227555281 | |
| 9,9.123932669691497 | |
| 10,7.753827235715137 | |
| 11,8.284921580798866 | |
| 12,8.368784370601428 | |
| 13,8.648691296436004 | |
| 14,7.968262484214747 | |
| 15,9.615280354255658 | |
| 16,8.436874177336145 | |
| 17,7.485839868213551 | |
| 18,9.33786587668085 | |
| 19,8.718505120547443 | |
| 20,8.423616183167304 | |
| 21,8.0918008973708 | |
| 22,8.799719726764605 | |
| 23,9.265722853181686 | |
| 24,8.331974823679284 | |
| 25,9.935813025540007 | |
| 26,8.226364415311977 | |
| 27,9.601727282627726 | |
| 28,9.583196144976998 | |
| 29,10.430763114083893 | |
| 30,9.436759174555814 | |