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
File size: 906 Bytes
0181745 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | {
"label_order": [
"baseline_llm",
"single_agent",
"per",
"broadcast",
"none"
],
"index_to_label": {
"0": "baseline_llm",
"1": "single_agent",
"2": "per",
"3": "broadcast",
"4": "none"
},
"label_to_index": {
"baseline_llm": 0,
"single_agent": 1,
"per": 2,
"broadcast": 3,
"none": 4
},
"note": "The estimator stores integer classes [0..4] with no embedded label map. This file IS that map. It is the paper's fixed cost order, NOT alphabetical order: decoding with sorted(labels) agrees with the released predictions on only 352 of 423 test rows, while this mapping agrees on 423 of 423.",
"verified": {
"check": "model.predict on reconstructed test features, decoded with index_to_label, compared to test_predictions.csv",
"n_test": 423,
"agreement_label_order": "423/423",
"agreement_sorted_order": "352/423"
}
} |