602 MB
8 files
Updated about 1 month ago
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.gitattributes1.52 kB
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README.md1.17 kB
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config.json1.34 kB
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model.safetensors598 MB
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special_tokens_map.json694 Bytes
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tokenizer.json3.58 MB
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tokenizer_config.json20.8 kB
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training_args.bin5.78 kB
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README.md

LocalLaws/LOCUS-Opacity

A ModernBERT regression model that scores local-ordinance text along the Opacity axis of the LOCUS (Local Ordinances Corpus, United States) dataset.

Fine-tuned from answerdotai/ModernBERT-base. The target is a TrueSkill mu distilled from pairwise LLM comparisons on the opacity axis, then z-score normalized across the training corpus.

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

tok = AutoTokenizer.from_pretrained("LocalLaws/LOCUS-Opacity")
model = AutoModelForSequenceClassification.from_pretrained("LocalLaws/LOCUS-Opacity")
model.eval()

text = "No person shall keep any swine within the city limits."
enc = tok(text, return_tensors="pt", truncation=True, max_length=2048)
with torch.no_grad():
    score = model(**enc).logits.squeeze(-1).item()
print(score)
Total size
602 MB
Files
8
Last updated
Jun 21
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