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/AAMRATECH/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/AAMRATECH/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/gru/models/AAMRATECH/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/gru/resolve/main/models/AAMRATECH/forecast_next_30.csv
661 Bytes
| step_ahead,prediction | |
| 1,15.683407418359907 | |
| 2,16.040824220381946 | |
| 3,15.968665934791158 | |
| 4,15.983930985873677 | |
| 5,16.145575955276296 | |
| 6,16.12580376092481 | |
| 7,16.278351414204945 | |
| 8,16.49760931111926 | |
| 9,16.984972215051535 | |
| 10,16.768545069309106 | |
| 11,16.6472227360587 | |
| 12,16.76230576780418 | |
| 13,16.57250571412901 | |
| 14,17.074716972161625 | |
| 15,17.06855729231054 | |
| 16,17.063843194703956 | |
| 17,17.468960028334095 | |
| 18,17.13469128584297 | |
| 19,17.38822057321734 | |
| 20,17.507799285192124 | |
| 21,17.348579213395098 | |
| 22,17.21807002838812 | |
| 23,17.28324918169818 | |
| 24,17.20809811332088 | |
| 25,17.536676231151276 | |
| 26,17.299284425120998 | |
| 27,17.358214672757768 | |
| 28,17.431017676876372 | |
| 29,17.822065952914834 | |
| 30,17.839187396798263 | |