Update README.md

README.md

@@ -29,14 +29,14 @@ pipeline_tag: text-classification
 ---
 
 #### Table of contents
-1. [Installation](#install)
+1. [Installation](#Installation)
 2. [Pre-processing](#preprocess)
 3. [Usage with `sentence-transformers`](#sentence)
 4. [Usage with `transformers`](#transformers)
-5. [Performance](#performance)
+5. [Performance](#Performance)
 
 
-## Installation<a name="install"></a>
+## Installation
   - Install `pyvi` to word segment:
 
 	- `pip install pyvi`
@@ -49,7 +49,7 @@ pipeline_tag: text-classification
 
 	- `pip install transformers`
 
-## Pre-processing<a name="preprocess"></a>
+## Pre-processing
 
 ```python
 from pyvi import ViTokenizer
@@ -67,7 +67,7 @@ tokenized_sentences = [ViTokenizer.tokenize(sent) for sent in sentences]
 tokenized_pairs = [[tokenized_query, sent] for sent in tokenized_sentences]
 ```
 
-## Usage with sentence-transformers<a name="sentence"></a>
+## Usage with sentence-transformers
 
 ```python
 from sentence_transformers import CrossEncoder
@@ -75,7 +75,7 @@ model = CrossEncoder('itdainb/vietnamese-cross-encoder', max_length=256)
 scores = model.predict(tokenized_pairs)
 ```
 
-## Usage with transformers<a name="transformers"></a>
+## Usage with transformers
 
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
@@ -94,7 +94,7 @@ with torch.no_grad():
     print(scores)
 ```
 
-## Performance<a name="performance"></a>
+## Performance
 In the following table, we provide various pre-trained Cross-Encoders together with their performance on the [MS MMarco Passage Reranking - Vi - Dev](https://huggingface.co/datasets/unicamp-dl/mmarco) dataset. 
 
 | Model-Name                                            | NDCG@3 | MRR@3 | NDCG@5 | MRR@5 | NDCG@10 | MRR@10 | Docs / Sec |