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update format in model card

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@@ -16,8 +16,8 @@ pipeline_tag: token-classification
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  # Multi-criteria BERT base Chinese with Lattice for Word Segmentation
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- This is a variant of the pre-trained model [BERT](https://github.com/google-research/bert) model
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- The model was pre-trained on texts in the Chinese language and fine-tuned for word segmentation.
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  This version of the model processes input texts with character-level with word-level incorporated with a lattice structure.
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  The scripts for the pre-training are available at [tchayintr/latte-ptm-ws](https://github.com/tchayintr/latte-ptm-ws).
@@ -28,7 +28,7 @@ The model architecture is described in this [paper](https://www.jstage.jst.go.jp
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  ## Training Data
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- The model is trained on multiple Chinese word segmented datasets, including CTB6, SIGHAN2005 (AS, CITYU, MSRA, PKU), SIGHAN2008 (SXU), and CNC.
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  The datasets can be accessed from [here](https://github.com/hankcs/multi-criteria-cws/tree/master/data).
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  ## Licenses
 
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  # Multi-criteria BERT base Chinese with Lattice for Word Segmentation
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+ This is a variant of the pre-trained model [BERT](https://github.com/google-research/bert) model.
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+ The model was pre-trained on texts in the Chinese language and fine-tuned for word segmentation based on [bert-base-chinese](https://huggingface.co/bert-base-chinese).
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  This version of the model processes input texts with character-level with word-level incorporated with a lattice structure.
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  The scripts for the pre-training are available at [tchayintr/latte-ptm-ws](https://github.com/tchayintr/latte-ptm-ws).
 
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  ## Training Data
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+ The model is trained on multiple Chinese word segmented datasets, including ctb6, sighan2005 (as, cityu, msra, pku), sighan2008 (sxu), and cnc.
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  The datasets can be accessed from [here](https://github.com/hankcs/multi-criteria-cws/tree/master/data).
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  ## Licenses