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/APEXFOODS/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/APEXFOODS/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/APEXFOODS/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/APEXFOODS/forecast_next_15.csv
206 Bytes
| step_ahead,prediction | |
| 1,199.28757 | |
| 2,201.6879 | |
| 3,203.61224 | |
| 4,193.67542 | |
| 5,198.04344 | |
| 6,194.94379 | |
| 7,197.13094 | |
| 8,194.08876 | |
| 9,192.98775 | |
| 10,194.03882 | |
| 11,193.30986 | |
| 12,191.83806 | |
| 13,187.57657 | |
| 14,191.42017 | |
| 15,186.4064 | |