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-# Blackboard CLS
-## V1.0
-**Model Details**
-
-- Developer: Wannaphong Phatthiyaphaibun
-- This report author: Wannaphong Phatthiyaphaibun
-- Model date: 2022-10-14
-- Model version: 1.0
-- Used in PyThaiNLP version: 3.2 +
-- Filename: `pythainlp/corpus/blackboard-cls_v1.0.crfsuite`
-- GitHub: [https://github.com/PyThaiNLP/pythainlp/issues/729](https://github.com/PyThaiNLP/pythainlp/issues/729)
-- CRF Model
-- License: CC0
-
-**Intended Use**
-
-- Segmenting Thai text into clauses (smaller than a sentence but bigger than a word)
-- Not suitable for other language or non-news domains.
-
-**Factors**
-
-- Based on known problems with thai natural Language processing.
-
-**Metrics**
-
-- Evaluation metrics include precision, recall and f1-score.
-
-**Training Data**
-
-Blackboard treebank
-
-**Evaluation Data**
-
-Blackboard treebank
-
-**Quantitative Analyses**
-
-```
-              precision    recall  f1-score   support
-
-       B_CLS       1.00      1.00      1.00     91698
-       E_CLS       1.00      1.00      1.00     91700
-       I_CLS       1.00      1.00      1.00    707795
-
-   micro avg       1.00      1.00      1.00    891193
-   macro avg       1.00      1.00      1.00    891193
-weighted avg       1.00      1.00      1.00    891193
- samples avg       1.00      1.00      1.00    891193
-```
-**Ethical Considerations**
-
-- It trains from Blackboard treebank. It is possible to have a bias from Blackboard treebank.
-
-**Caveats and Recommendations**
-
-- The user must perform word segmentation first before using this model.
-- Thai text only