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_30.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 398 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/APEXFOODS/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/seperate/models/APEXFOODS/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/seperate/resolve/main/models/APEXFOODS/forecast_next_30.csv
398 Bytes
| step_ahead,prediction | |
| 1,200.0613 | |
| 2,200.13744 | |
| 3,198.57385 | |
| 4,192.30681 | |
| 5,199.62746 | |
| 6,189.9699 | |
| 7,192.9868 | |
| 8,191.77643 | |
| 9,191.56004 | |
| 10,183.04643 | |
| 11,189.29185 | |
| 12,184.99069 | |
| 13,189.66064 | |
| 14,186.71115 | |
| 15,193.88542 | |
| 16,176.72882 | |
| 17,189.74324 | |
| 18,182.0753 | |
| 19,188.30669 | |
| 20,181.89668 | |
| 21,179.41275 | |
| 22,178.30096 | |
| 23,178.83618 | |
| 24,177.9452 | |
| 25,182.79361 | |
| 26,172.38863 | |
| 27,171.28172 | |
| 28,183.75888 | |
| 29,179.43463 | |
| 30,180.56734 | |