Text Classification
Scikit-learn
Joblib
ai-systems
routing
orchestration
agents
memory
validation
interoperability
physical-ai
Instructions to use ai-systems/system-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use ai-systems/system-router with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("ai-systems/system-router", "sklearn_model.joblib") ) # 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 example_usage.py from ai-systems/system-router: direct link, hf CLI and curl.
- Browser
- Download file 428 Bytes
-
https://huggingface.co/ai-systems/system-router/resolve/main/example_usage.py
- Command line
-
hf download hf://ai-systems/system-router/example_usage.py
-
curl -L -o example_usage.py https://huggingface.co/ai-systems/system-router/resolve/main/example_usage.py
428 Bytes
| from joblib import load | |
| router = load("system-router.joblib") | |
| queries = [ | |
| "Use a human approval step before an agent can deploy code", | |
| "Route hard reasoning tasks to a stronger model", | |
| "Store long-term memories for a persistent agent" | |
| ] | |
| for q in queries: | |
| label = router.predict([q])[0] | |
| scores = router.predict_proba([q])[0] | |
| confidence = scores.max() | |
| print(f"{q}\n -> {label} ({confidence:.2f})") | |