Instructions to use syreeta/CodeCrusaders with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use syreeta/CodeCrusaders with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("syreeta/CodeCrusaders", "voting.pickle") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Download config.json from syreeta/CodeCrusaders: direct link, hf CLI and curl.
- Browser
- Download file 952 Bytes
-
https://huggingface.co/syreeta/CodeCrusaders/resolve/main/config.json
- Command line
-
hf download hf://syreeta/CodeCrusaders/config.json
-
curl -L -o config.json https://huggingface.co/syreeta/CodeCrusaders/resolve/main/config.json
952 Bytes
| { | |
| "sklearn": { | |
| "columns": [ | |
| "memory_GB", | |
| "network_log10_MBps", | |
| "local_IO_log10_MBps", | |
| "NFS_IO_log10_MBps" | |
| ], | |
| "environment": [ | |
| "scikit-learn=1.6.1" | |
| ], | |
| "example_input": { | |
| "NFS_IO_log10_MBps": [ | |
| -3.0, | |
| -1.4805, | |
| -3.0 | |
| ], | |
| "local_IO_log10_MBps": [ | |
| -0.8381, | |
| 0.0968, | |
| -0.9018 | |
| ], | |
| "memory_GB": [ | |
| 43.5205, | |
| 10.3542, | |
| 88.2232 | |
| ], | |
| "network_log10_MBps": [ | |
| -1.1597, | |
| 0.8827, | |
| -0.519 | |
| ] | |
| }, | |
| "model": { | |
| "file": "voting.pickle" | |
| }, | |
| "model_format": "pickle", | |
| "task": "tabular-classification" | |
| } | |
| } |