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README.md

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 ## Model Overview
 
-This model, **bert-conll-ner**, is a fine-tuned version of [`bert-base-uncased`](https://huggingface.co/google-bert/bert-base-chinese) trained for the task of Named Entity Recognition (NER) using the [CoNLL-2003](https://huggingface.co/datasets/eriktks/conll2003) dataset. It is designed to identify and classify entities in text, such as **person names (PER)**, **organizations (ORG)**, **locations (LOC)**, and **miscellaneous (MISC)** entities.
+This model, **bert-conll-ner**, is a fine-tuned version of `bert-base-uncased` trained for the task of Named Entity Recognition (NER) using the [CoNLL-2003](https://huggingface.co/datasets/eriktks/conll2003) dataset. It is designed to identify and classify entities in text, such as **person names (PER)**, **organizations (ORG)**, **locations (LOC)**, and **miscellaneous (MISC)** entities.
 
 ### Model Architecture
 - **Base Model**: BERT (Bidirectional Encoder Representations from Transformers) with the `bert-base-uncased` architecture.