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tibetan-outline-boundary-crf-full
openpecha/tibetan-outline-boundary-crf-full
tibetan-outline-boundary-crf-full is a token classification model from openpecha. Use it when you need labels on individual words, such as names. It is set up for sklearn-crfsuite. The card lists the license as apache-2.0.
Production CRF model for Tibetan text boundary detection, trained on the full snippet corpus (82,560 snippets).
Access
Public
Updated Jun 5, 2026
Repo size
1.2 MB
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0
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Repo makeup
Click a slice to open those files.
.pkl1.2 MB · 100%
At a glance
- Task
- Token Classification
- Library
- sklearn-crfsuite
- License
- apache-2.0
- Access
- Public
- Created
- Jun 5, 2026
- Updated
- Jun 5, 2026
- SHA
- 08fa4eb0
Model card
From the Hugging Face model README
Tibetan Outline Boundary CRF (Full)
Production CRF model for Tibetan text boundary detection, trained on the full snippet corpus (82,560 snippets).
Evaluation (unique benchmark, 31,591 snippets, ±15 chars)
| Precision | Recall | F1 |
|---|---|---|
| 0.718 | 0.475 | 0.571 |
Note: trained including unique-benchmark strings — use for production recall, not unbiased benchmark reporting.
Related repos
- Training data: ganga4364/tibetan-outline-boundary-snippets-full
- Unbiased model: ganga4364/tibetan-outline-boundary-crf-unbiased
Usage
pip install "outline-detection[crf]"
hf download ganga4364/tibetan-outline-boundary-crf-full boundary_crf.pkl --local-dir ./models
outline-detect crf predict input.txt --model ./models/boundary_crf.pkl -o output.txt
from outline_detection.crf import CRFBoundaryDetector
det = CRFBoundaryDetector()
det.load("boundary_crf.pkl")
positions = det.predict_positions(clean_tibetan_text)
Security
Pickle files load executable objects. Only use models from this trusted repository.
- Task
- Token Classification
- Library
- sklearn-crfsuite
- License
- apache-2.0
- Languages
- bo
- Created
- Jun 5, 2026
- Updated
- Jun 5, 2026