Scikit-learn
Joblib
English
protocol-routing
llm-routing
multi-agent-systems
cost-aware-inference
protocol-selection
calibration
reasoning
reproducibility
emnlp2026
Instructions to use AgentsSci/EMNLP_Cost-Aware-Protocol-Routing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use AgentsSci/EMNLP_Cost-Aware-Protocol-Routing with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("AgentsSci/EMNLP_Cost-Aware-Protocol-Routing", "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
Publish the trained metadata-only router checkpoint with its fitted feature builders, verified label map, and a runnable example
0181745 verified Download router_metadata_only/class_recalls.csv from AgentsSci/EMNLP_Cost-Aware-Protocol-Routing: direct link, hf CLI and curl.
- Browser
- Download file 525 Bytes
-
https://huggingface.co/AgentsSci/EMNLP_Cost-Aware-Protocol-Routing/resolve/main/router_metadata_only/class_recalls.csv
- Command line
-
hf download hf://AgentsSci/EMNLP_Cost-Aware-Protocol-Routing/router_metadata_only/class_recalls.csv
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curl -L -o class_recalls.csv https://huggingface.co/AgentsSci/EMNLP_Cost-Aware-Protocol-Routing/resolve/main/router_metadata_only/class_recalls.csv
525 Bytes
| model_name,split,label,recall | |
| metadata_only_logreg,dev,baseline_llm,0.8860759493670886 | |
| metadata_only_logreg,dev,single_agent,0.1875 | |
| metadata_only_logreg,dev,per,0.1388888888888889 | |
| metadata_only_logreg,dev,broadcast,0.0 | |
| metadata_only_logreg,dev,none,0.13333333333333333 | |
| metadata_only_logreg,test,baseline_llm,0.9411764705882353 | |
| metadata_only_logreg,test,single_agent,0.13402061855670103 | |
| metadata_only_logreg,test,per,0.07894736842105263 | |
| metadata_only_logreg,test,broadcast,0.0 | |
| metadata_only_logreg,test,none,0.0625 | |