Update README.md

README.md

@@ -2,14 +2,13 @@
 
 This is a roBERTa-base model trained on ~58M tweets, described and evaluated in the [_TweetEval_ benchmark (Findings of EMNLP 2020)](https://arxiv.org/pdf/2010.12421.pdf). To evaluate this and other LMs on Twitter-specific data, please refer to the [Tweeteval official repository](https://github.com/cardiffnlp/tweeteval).
 
-
 ## Example Masked Language Model 
 
 ```python
 from transformers import pipeline, AutoTokenizer
 import numpy as np
 
-MODEL = "cardiffnlp/roberta-base-rt"
+MODEL = "cardiffnlp/twitter-roberta-base"
 fill_mask = pipeline("fill-mask", model=MODEL, tokenizer=MODEL)
 tokenizer = AutoTokenizer.from_pretrained(MODEL)
 
@@ -29,6 +28,8 @@ for text in texts:
     print_candidates()
 ```
 
+Output: 
+
 ```
 ------------------------------
 I am so <mask> 😊
@@ -44,4 +45,7 @@ I am so <mask> 😢
 3)  tired 0.138
 4)  sick 0.0278
 5)  hungry 0.0232
-```
+```
+
+## Example Feature Extraction 
+TODO