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/ARAMITCEM/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/ARAMITCEM/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/ARAMITCEM/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/ARAMITCEM/forecast_next_15.csv
204 Bytes
| step_ahead,prediction | |
| 1,13.612754 | |
| 2,13.813379 | |
| 3,13.821382 | |
| 4,14.02099 | |
| 5,13.958803 | |
| 6,13.908464 | |
| 7,14.118064 | |
| 8,14.078604 | |
| 9,13.677328 | |
| 10,14.0095 | |
| 11,13.967227 | |
| 12,14.057209 | |
| 13,14.177817 | |
| 14,14.39464 | |
| 15,14.434937 | |