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/ACMEPL/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/ACMEPL/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/ACMEPL/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/ACMEPL/forecast_next_15.csv
205 Bytes
| step_ahead,prediction | |
| 1,14.121644 | |
| 2,14.403332 | |
| 3,14.51594 | |
| 4,14.84966 | |
| 5,13.870608 | |
| 6,13.349224 | |
| 7,14.276577 | |
| 8,13.75221 | |
| 9,14.166493 | |
| 10,14.648097 | |
| 11,15.154206 | |
| 12,14.458702 | |
| 13,13.544607 | |
| 14,13.677539 | |
| 15,14.010598 | |