How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="Supreeth/DeBERTa-Twitter-Emotion-Classification")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("Supreeth/DeBERTa-Twitter-Emotion-Classification")
model = AutoModelForSequenceClassification.from_pretrained("Supreeth/DeBERTa-Twitter-Emotion-Classification")
Quick Links

Label - Emotion Table

Emotion LABEL
Anger LABEL_0
Boredom LABEL_1
Empty LABEL_2
Enthusiasm LABEL_3
Fear LABEL_4
Fun LABEL_5
Happiness LABEL_6
Hate LABEL_7
Joy LABEL_8
Love LABEL_9
Neutral LABEL_10
Relief LABEL_11
Sadness LABEL_12
Surprise LABEL_13
Worry LABEL_14
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Model size
0.1B params
Tensor type
I64
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F32
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