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_15.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 205 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/AMCL(PRAN)/forecast_next_15.csv
- Command line
-
hf download 'hf://StockCast/seperate/models/AMCL(PRAN)/forecast_next_15.csv'
-
curl -L -o forecast_next_15.csv 'https://huggingface.co/StockCast/seperate/resolve/main/models/AMCL(PRAN)/forecast_next_15.csv'
205 Bytes
| step_ahead,prediction | |
| 1,225.66255 | |
| 2,224.8979 | |
| 3,224.79419 | |
| 4,224.82681 | |
| 5,226.21536 | |
| 6,224.04944 | |
| 7,225.66428 | |
| 8,225.72076 | |
| 9,224.1706 | |
| 10,221.44914 | |
| 11,222.24944 | |
| 12,222.72665 | |
| 13,223.22867 | |
| 14,223.6965 | |
| 15,222.70422 | |