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_30.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 403 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/00DSMEX/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/seperate/models/00DSMEX/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/seperate/resolve/main/models/00DSMEX/forecast_next_30.csv
403 Bytes
| step_ahead,prediction | |
| 1,1087.0573 | |
| 2,1078.9406 | |
| 3,1101.3411 | |
| 4,1085.8003 | |
| 5,1090.4694 | |
| 6,1086.2751 | |
| 7,1088.5126 | |
| 8,1111.2955 | |
| 9,1096.8322 | |
| 10,1110.4283 | |
| 11,1109.2482 | |
| 12,1090.2775 | |
| 13,1101.2715 | |
| 14,1088.7543 | |
| 15,1083.0896 | |
| 16,1095.7605 | |
| 17,1101.9291 | |
| 18,1092.1516 | |
| 19,1115.6122 | |
| 20,1116.3724 | |
| 21,1118.4677 | |
| 22,1105.6433 | |
| 23,1114.5231 | |
| 24,1111.3723 | |
| 25,1122.9829 | |
| 26,1134.7515 | |
| 27,1107.8666 | |
| 28,1124.3096 | |
| 29,1119.6321 | |
| 30,1127.7838 | |