DeBERTa V3 - Multi-label Emotion Classifier
This model is a fine-tuned version of microsoft/deberta-v3-base for multi-label emotion classification.
Model Details
- Base model:
DeBERTa V3 - Task: Multi-label emotion detection
- Architecture:
DebertaV2ForSequenceClassification - Number of labels: 14
- Format:
safetensors
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
tokenizer = AutoTokenizer.from_pretrained("PuroFuro/deberta-v3-emotion-multilabel")
model = AutoModelForSequenceClassification.from_pretrained("PuroFuro/deberta-v3-emotion-multilabel")
inputs = tokenizer("I feel nervous but hopeful.", return_tensors="pt")
outputs = model(**inputs)
probs = torch.sigmoid(outputs.logits)
print(probs)
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