Add metadata, links

README.md

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+---
+datasets:
+- tweet_eval
+language:
+- en
+---
 # Twitter-roBERTa-base for Sentiment Analysis
 
 This is a roBERTa-base model trained on ~58M tweets and finetuned for sentiment analysis with the TweetEval benchmark. This model is suitable for English (for a similar multilingual model, see [XLM-T](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment)).
@@ -10,7 +16,8 @@ This is a roBERTa-base model trained on ~58M tweets and finetuned for sentiment
 1 -> Neutral;
 2 -> Positive
 
-<b>New!</b> We just released a new sentiment analysis model trained on more recent and a larger quantity of tweets. See [twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) for more details.
+<b>New!</b> We just released a new sentiment analysis model trained on more recent and a larger quantity of tweets. 
+See [twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) and [TweetNLP](https://tweetnlp.org) for more details.
 
 ## Example of classification
 
@@ -87,4 +94,4 @@ Output:
 1) positive 0.8466
 2) neutral 0.1458
 3) negative 0.0076
-```
+```