Update README.md

README.md

@@ -254,7 +254,7 @@ Our training dataset. Because of label ambiguity, with UIT-VSMEC, UIT-ViCTSD, VO
             <td>65.54</td>
         </tr>
         <tr align="center">
-            <td align="left"><b>5CD-AI/Vietnamese-sentiment-visobert-base</td>
+            <td align="left"><b>5CD-AI/Vietnamese-Sentiment-visobert</td>
             <td><b>88.06</td>
             <td><b>88.16</td>
             <td><b>88.06</td>
@@ -318,7 +318,7 @@ Our training dataset. Because of label ambiguity, with UIT-VSMEC, UIT-ViCTSD, VO
             <td>65.70</td>
         </tr>
         <tr align="center">
-            <td align="left"><b>5CD-AI/Vietnamese-sentiment-visobert-base</td>
+            <td align="left"><b>5CD-AI/Vietnamese-Sentiment-visobert</td>
             <td><b>94.35</td>
             <td><b>94.74</td>
             <td><b>94.35</td>
@@ -346,7 +346,7 @@ Install `transformers` package:
 ### Pipeline
 ```python
 from transformers import pipeline
-model_path = '5CD-AI/vietnamese-sentiment-visobert'
+model_path = '5CD-AI/Vietnamese-Sentiment-visobert'
 sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
 sentiment_task("Miếng dán dễ xước , ko khít với dt 11 prm")
 ```
@@ -450,7 +450,7 @@ import numpy as np
 import torch
 
 #### Load model
-model_path = '5CD-AI/Vietnamese-sentiment-visobert-base'
+model_path = '5CD-AI/Vietnamese-Sentiment-visobert'
 tokenizer = AutoTokenizer.from_pretrained(model_path)
 config = AutoConfig.from_pretrained(model_path)
 model = AutoModelForSequenceClassification.from_pretrained(model_path).to("cuda")