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/AMANFEED/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/AMANFEED/forecast_next_15.csv
- Command line
-
hf download hf://StockCast/seperate/models/AMANFEED/forecast_next_15.csv
-
curl -L -o forecast_next_15.csv https://huggingface.co/StockCast/seperate/resolve/main/models/AMANFEED/forecast_next_15.csv
206 Bytes
| step_ahead,prediction | |
| 1,25.447098 | |
| 2,25.531649 | |
| 3,27.126335 | |
| 4,26.02098 | |
| 5,25.575666 | |
| 6,25.303606 | |
| 7,25.909477 | |
| 8,26.156448 | |
| 9,25.80005 | |
| 10,26.009502 | |
| 11,25.064213 | |
| 12,26.245157 | |
| 13,25.959541 | |
| 14,26.368423 | |
| 15,26.329874 | |