Update README.md

README.md

@@ -3,31 +3,22 @@ language: en
 tags:
 - text-classification
 - tensorflow
-- roberta
-datasets:
-- go_emotions
 license: mit
 ---
-
-## What is the GoEmotions Dataset?
-
-The dataset is comprised of 58000 Reddit comments with 28 emotions.
-
-- admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pride, realization, relief, remorse, sadness, surprise
 ## Usage
 
 ```python
 
 from transformers import RobertaTokenizerFast, TFRobertaForSequenceClassification, pipeline
 
-tokenizer = RobertaTokenizerFast.from_pretrained("cappuch/EmoRoBERTa_Retrain")
-model = TFRobertaForSequenceClassification.from_pretrained("cappuch/EmoRoBERTa_Retrain")
+tokenizer = RobertaTokenizerFast.from_pretrained("cappuch/Emotions_BERT")
+model = TFRobertaForSequenceClassification.from_pretrained("cappuch/Emotions_BERT")
 
-emotion = pipeline('sentiment-analysis', 
-                    model='cappuch/EmoRoBERTa_Retrain')
+classific = pipeline('sentiment-analysis', 
+                    model='cappuch/Emotions_BERT')
 
-emotion_labels = emotion("Hello!")
-print(emotion_labels)
+labels = classific("Hello!")
+print(labels)
 
 #[{'label': 'neutral', 'score': 0.9964383244514465}]
 ```