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/00DSMEX/forecast_next_15.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 205 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/00DSMEX/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/00DSMEX/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/00DSMEX/forecast_next_15.csv
205 Bytes
| step_ahead,prediction | |
| 1,1087.6174 | |
| 2,1060.048 | |
| 3,1044.207 | |
| 4,1085.3478 | |
| 5,1075.4708 | |
| 6,1074.5752 | |
| 7,1075.1544 | |
| 8,1080.6149 | |
| 9,1086.0792 | |
| 10,1067.6714 | |
| 11,1089.0305 | |
| 12,1079.008 | |
| 13,1092.3773 | |
| 14,1064.6833 | |
| 15,1105.9785 | |