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/ARAMIT/forecast_next_15.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 206 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/ARAMIT/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/ARAMIT/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/ARAMIT/forecast_next_15.csv
206 Bytes
| step_ahead,prediction | |
| 1,199.91742 | |
| 2,199.56667 | |
| 3,200.24232 | |
| 4,200.0658 | |
| 5,200.2221 | |
| 6,201.57817 | |
| 7,202.09949 | |
| 8,201.25958 | |
| 9,200.78568 | |
| 10,200.38185 | |
| 11,201.43794 | |
| 12,201.77112 | |
| 13,202.30885 | |
| 14,203.11055 | |
| 15,202.91087 | |