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/APOLOISPAT/forecast_next_30.csv from StockCast/gru: direct link, hf CLI and curl.
- Browser
- Download file 642 Bytes
-
https://huggingface.co/StockCast/gru/resolve/main/models/APOLOISPAT/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/gru/models/APOLOISPAT/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/gru/resolve/main/models/APOLOISPAT/forecast_next_30.csv
642 Bytes
| step_ahead,prediction | |
| 1,4.479456753252832 | |
| 2,4.181179783035592 | |
| 3,4.21772941304905 | |
| 4,4.387846062290963 | |
| 5,5.142792162671356 | |
| 6,4.687204177813096 | |
| 7,5.292611926742102 | |
| 8,4.397124710554769 | |
| 9,4.464698915778013 | |
| 10,4.310086780311729 | |
| 11,4.997776819431508 | |
| 12,5.0965075606162955 | |
| 13,5.0942959061906805 | |
| 14,4.793438996386444 | |
| 15,5.503346639542799 | |
| 16,3.787927608551015 | |
| 17,4.382122774841059 | |
| 18,4.118869820644212 | |
| 19,4.893779503266078 | |
| 20,5.397686695643526 | |
| 21,3.700359600325035 | |
| 22,4.685139837452035 | |
| 23,4.296476165690548 | |
| 24,4.185705512087375 | |
| 25,4.781373624677219 | |
| 26,4.6850578235533 | |
| 27,4.595029689883854 | |
| 28,5.123043915500498 | |
| 29,4.6833693478371545 | |
| 30,4.39392772326994 | |