PISCO Router
A routing classifier for PISCO (COCOM architecture) that decides at inference time whether compressed context is sufficient or whether to fall back to the full context.
Trained with overflowguard on SQuAD using an LLM judge (DeepSeek) for evaluation, with 5-fold stratified CV for threshold selection (Youden's J statistic).
Usage
from examples.train_pisco import PiscoRouter
# Load base model + routing classifier in one call
router = PiscoRouter.from_pretrained("wexumin/pisco-7b-router")
router.park_gpu()
# Auto-routing: classifier decides compressed vs full
result = router.run_pipeline("long document text...", query="what is X?")
print(result["prediction"]) # answer
print(result["mode"]) # "compressed" or "full"
print(result["tokens_saved"])
What's in this repo
router_config.jsonโ base model path + routing thresholdrouting_clf.ptโ classifier weights (2-layer MLP, ~2K params)
The base PISCO model is loaded automatically from naver/pisco-mistral. This repo only contains the lightweight routing classifier on top.
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐ Ask for provider support
Model tree for wexumin/pisco-7b-router
Base model
mistralai/Mistral-7B-Instruct-v0.2 Finetuned
naver/pisco-mistral