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/AAMRATECH/forecast_next_7.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 105 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/AAMRATECH/forecast_next_7.csv
- Command line
-
hf download hf://StockCast/seperate/models/AAMRATECH/forecast_next_7.csv
-
curl -L -o forecast_next_7.csv https://huggingface.co/StockCast/seperate/resolve/main/models/AAMRATECH/forecast_next_7.csv
105 Bytes
| step_ahead,prediction | |
| 1,13.241639 | |
| 2,13.709873 | |
| 3,13.586636 | |
| 4,13.441594 | |
| 5,13.822107 | |
| 6,13.686663 | |
| 7,14.03436 | |