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/AFCAGRO/forecast_next_15.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 202 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/AFCAGRO/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/AFCAGRO/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/AFCAGRO/forecast_next_15.csv
202 Bytes
| step_ahead,prediction | |
| 1,10.517843 | |
| 2,10.134311 | |
| 3,10.567864 | |
| 4,10.063845 | |
| 5,11.521808 | |
| 6,9.117423 | |
| 7,11.05558 | |
| 8,9.813808 | |
| 9,12.362136 | |
| 10,11.066218 | |
| 11,9.739382 | |
| 12,9.705425 | |
| 13,10.405668 | |
| 14,10.585986 | |
| 15,9.375314 | |