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/ACFL/forecast_next_15.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 204 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/ACFL/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/ACFL/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/ACFL/forecast_next_15.csv
204 Bytes
| step_ahead,prediction | |
| 1,18.58747 | |
| 2,18.877945 | |
| 3,19.34548 | |
| 4,19.82055 | |
| 5,18.631819 | |
| 6,19.336681 | |
| 7,19.61387 | |
| 8,19.201918 | |
| 9,18.546968 | |
| 10,19.670797 | |
| 11,19.771132 | |
| 12,19.358135 | |
| 13,20.143642 | |
| 14,19.495264 | |
| 15,20.758266 | |