Instructions to use StockCast/seperate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use StockCast/seperate 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/seperate") - Notebooks
- Google Colab
- Kaggle
Download models/ABBANK/forecast_next_15.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 197 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/ABBANK/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/ABBANK/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/ABBANK/forecast_next_15.csv
197 Bytes
| step_ahead,prediction | |
| 1,8.605017 | |
| 2,8.763127 | |
| 3,7.5376687 | |
| 4,7.7751994 | |
| 5,8.630006 | |
| 6,7.7549253 | |
| 7,8.234796 | |
| 8,8.385836 | |
| 9,8.876022 | |
| 10,7.840001 | |
| 11,7.6616764 | |
| 12,7.7484937 | |
| 13,8.60158 | |
| 14,8.19521 | |
| 15,7.1672683 | |