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RESEARCH-EMPRM
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Model Details
Model Provider
RESEARCH-EMPRM
Model Tree
Qwen/Qwen3-VL-8B-Instruct
Input Modalities
Output Modalities
Supported Functionality
a2_support_s0 (RESEARCH-EMPRM/emprm-v2-a2_support_s0). Task-data sha256 ddd7be2d3ddf…, pair-data runs/v2/data/stageB_pairs_g/pairs.jsonl.Chart gates met in both passes; external targets not met in the deployed pass. Not deployed; a twelve-benchmark Best-of-8 run is started only after the author's decision.
RESEARCH-EMPRM/emprm-sync-20260910 → results/**/runs/v2/train/stageB_g_s0/, results/**/runs/v2/e2/stageB_g_s0__*.json, configs/ablations/stageB_g_s0.yaml, EXPERIMENT_REGISTRY.csv (rows tagged with this adapter), CURRENT.md and WRITER_SYNC_BUNDLE.md (what the deployed scorer computes; which arm is which).RESEARCH-EMPRM/emprm-v2 predates this arm and does not contain it.python
from transformers import AutoModelForImageTextToText, AutoProcessorfrom peft import PeftModelbase = AutoModelForImageTextToText.from_pretrained("Qwen/Qwen3-VL-8B-Instruct", dtype="bfloat16", device_map="cuda")model = PeftModel.from_pretrained(base, "RESEARCH-EMPRM/emprm-v2-stageB_g_s0")processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-8B-Instruct")
adapter_config.json records the local path the adapter was trained from; pass the base model explicitly as above. The scorer (scoring.Scorer.score_grounded, family grounded, aggregation product) and its prompts are in code/ of the sync dataset.