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/ACMELAB/forecast_next_15.csv from StockCast/seperate: direct link, hf CLI and curl.
- Browser
- Download file 194 Bytes
-
https://huggingface.co/StockCast/seperate/resolve/main/models/ACMELAB/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/ACMELAB/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/ACMELAB/forecast_next_15.csv
194 Bytes
| step_ahead,prediction | |
| 1,77.26194 | |
| 2,76.93502 | |
| 3,77.57249 | |
| 4,77.16463 | |
| 5,76.350624 | |
| 6,77.42619 | |
| 7,77.83696 | |
| 8,77.65142 | |
| 9,76.833664 | |
| 10,77.75404 | |
| 11,77.35156 | |
| 12,77.36346 | |
| 13,76.59452 | |
| 14,77.66016 | |
| 15,77.4444 | |