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/ARAMIT/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/ARAMIT/forecast_next_30.csv
- Command line
-
hf download hf://StockCast/seperate/models/ARAMIT/forecast_next_30.csv
-
curl -L -o forecast_next_30.csv https://huggingface.co/StockCast/seperate/resolve/main/models/ARAMIT/forecast_next_30.csv
398 Bytes
| step_ahead,prediction | |
| 1,200.77832 | |
| 2,201.12321 | |
| 3,201.25697 | |
| 4,201.58316 | |
| 5,206.77594 | |
| 6,203.91946 | |
| 7,202.74484 | |
| 8,199.94386 | |
| 9,201.08775 | |
| 10,202.88226 | |
| 11,198.5703 | |
| 12,200.66565 | |
| 13,204.08173 | |
| 14,204.46999 | |
| 15,204.22554 | |
| 16,203.49702 | |
| 17,203.69606 | |
| 18,204.00677 | |
| 19,205.66313 | |
| 20,206.5936 | |
| 21,206.1194 | |
| 22,206.50363 | |
| 23,206.77924 | |
| 24,205.53394 | |
| 25,206.75446 | |
| 26,205.3312 | |
| 27,204.8821 | |
| 28,204.14064 | |
| 29,205.15126 | |
| 30,206.51447 | |