Update README.md

README.md

@@ -1,15 +1,17 @@
 ---
+language:
+- en
 license: mit
 datasets:
 - cardiffnlp/super_tweeteval
-language:
-- en
 pipeline_tag: text-classification
+widget:
+- text: "In this bullpen, you should be able to ask why and understand why we do the things we do.' @Trisha_Ford 😍 #pitchstock2020 @user</s>Castro needs to be the last bullpen guy to pitch.</s>bullpen"
 ---
 # cardiffnlp/twitter-roberta-large-tempo-wic-latest
 
 This is a RoBERTa-large model trained on 154M tweets until the end of December 2022 and finetuned for meaning shift detection (binary classification) on the _TempoWIC_ dataset of [SuperTweetEval](https://huggingface.co/datasets/cardiffnlp/super_tweeteval).
-The original Twitter-based RoBERTa model can be found [here](https://huggingface.co/cardiffnlp/twitter-roberta-large-2022-154m).
+The original Twitter-larged RoBERTa model can be found [here](https://huggingface.co/cardiffnlp/twitter-roberta-large-2022-154m).
 
 ## Labels
   "id2label": {
@@ -20,13 +22,14 @@ The original Twitter-based RoBERTa model can be found [here](https://huggingface
 ## Example
 ```python
 from transformers import pipeline
-text_1 = "We don't like the search and frisk so this bitch in neutral"
-text_2 = "who the fuck is listening to mike bloomberg railing in 'bernie bros'? mr stop and frisk, literally turned the police on occupy wall street, rnc protestors, and new york muslims. get the fuck out"
-text_input = f"{text_1}</s>{text_2}"
+text_1 = "'In this bullpen, you should be able to ask why and understand why we do the things we do.' @Trisha_Ford 😍 #pitchstock2020 @user"
+text_2 = "Castro needs to be the last bullpen guy to pitch."
+target = "bullpen"
+text_input = f"{text_1}</s>{text_2}</s>{target}"
 
 pipe = pipeline('text-classification', model="cardiffnlp/twitter-roberta-large-tempo-wic-latest")
 pipe(text_input)
->> [{'label': 'yes', 'score': 0.9994196891784668}]
+>> [{'label': 'yes', 'score': 0.9783471822738647}]
 ```
 
 ## Citation Information