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/AIL/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/AIL/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/gru/models/AIL/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/gru/resolve/main/models/AIL/forecast_next_30.csv
639 Bytes
| step_ahead,prediction | |
| 1,80.39857546515455 | |
| 2,76.46911002941978 | |
| 3,80.6360564035201 | |
| 4,79.42335021152383 | |
| 5,78.91905190219677 | |
| 6,79.18005572886804 | |
| 7,76.88551846813438 | |
| 8,74.7150063290968 | |
| 9,76.71222537131241 | |
| 10,78.27427311250031 | |
| 11,76.7985797496692 | |
| 12,76.51438145942467 | |
| 13,76.50054923335477 | |
| 14,78.37697621812379 | |
| 15,76.32190750517553 | |
| 16,75.57025845448393 | |
| 17,76.78089173193504 | |
| 18,75.16821539887245 | |
| 19,74.98576053159161 | |
| 20,75.79719141410423 | |
| 21,74.30591707013426 | |
| 22,74.07503021795559 | |
| 23,75.14546878720711 | |
| 24,75.67078627941187 | |
| 25,73.66579167502375 | |
| 26,73.93769749671033 | |
| 27,73.2985104579783 | |
| 28,72.02527601431447 | |
| 29,71.35880413125032 | |
| 30,73.28275886658881 | |