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/AMCL(PRAN)/forecast_next_30.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 397 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/AMCL(PRAN)/forecast_next_30.csv
- Command line
-
hf download 'hf://StockCast/seperate/models/AMCL(PRAN)/forecast_next_30.csv'
-
curl -L -o forecast_next_30.csv 'https://huggingface.co/StockCast/seperate/resolve/main/models/AMCL(PRAN)/forecast_next_30.csv'
397 Bytes
| step_ahead,prediction | |
| 1,230.87978 | |
| 2,229.564 | |
| 3,228.91582 | |
| 4,228.95111 | |
| 5,230.24324 | |
| 6,227.68579 | |
| 7,227.52083 | |
| 8,229.50163 | |
| 9,228.51723 | |
| 10,228.25838 | |
| 11,227.9416 | |
| 12,227.9687 | |
| 13,226.64717 | |
| 14,226.7099 | |
| 15,227.97786 | |
| 16,225.31847 | |
| 17,229.39758 | |
| 18,227.38126 | |
| 19,228.40927 | |
| 20,223.4756 | |
| 21,225.49791 | |
| 22,225.61836 | |
| 23,225.75761 | |
| 24,224.99168 | |
| 25,222.60274 | |
| 26,225.21165 | |
| 27,225.83293 | |
| 28,224.61133 | |
| 29,224.72781 | |
| 30,224.54631 | |