Update README.md

README.md

@@ -5,13 +5,13 @@ language:
 - zh
 pipeline_tag: token-classification
 ---
-# BertChunker
+# bert-chunker
 
 [Paper](https://github.com/jackfsuia/BertChunker/blob/main/main.pdf) | [Github](https://github.com/jackfsuia/BertChunker)
 
 ## Introduction
 
-BertChunker is a text chunker based on BERT with a classifier head to predict the start token of chunks (for use in RAG, etc), and using a sliding window it cuts documents of any size into chunks. It was finetuned on [nreimers/MiniLM-L6-H384-uncased](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2). The whole training lasted for 10 minutes on a Nvidia P40 GPU on a 50 MB synthetized dataset.
+bert-chunker is a text chunker based on BERT with a classifier head to predict the start token of chunks (for use in RAG, etc), and using a sliding window it cuts documents of any size into chunks. It was finetuned on [nreimers/MiniLM-L6-H384-uncased](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2). The whole training lasted for 10 minutes on a Nvidia P40 GPU on a 50 MB synthetized dataset.
 
 This repo includes model checkpoint, BertChunker class definition file and all the other files needed.
 
@@ -25,7 +25,7 @@ from modeling_bertchunker import BertChunker
 
 # load bert tokenizer
 tokenizer = AutoTokenizer.from_pretrained(
-    "tim1900/BertChunker",
+    "tim1900/bert-chunker",
     padding_side="right",
     model_max_length=255,
     trust_remote_code=True,
@@ -33,7 +33,7 @@ tokenizer = AutoTokenizer.from_pretrained(
 
 # load MiniLM-L6-H384-uncased bert config
 config = AutoConfig.from_pretrained(
-    "tim1900/BertChunker",
+    "tim1900/bert-chunker",
     trust_remote_code=True,
 )