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+ ---
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+ language: en
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+ tags:
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+ - vad
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+ - emotion
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+ - bert
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+ license: mit
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+ model-index:
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+ - name: vad-bert
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+ results: []
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+ datasets:
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+ - reallycarlaost/emobank
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+ base_model:
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+ - google-bert/bert-base-uncased
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+ ---
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+
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+ # vad-bert
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+
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+ A BERT-based model fine-tuned to predict **Valence, Arousal, and Dominance (VAD)** values from text.
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+
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+ ## Intended use
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+
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+ This model is intended for regression tasks on emotional dimensions. It outputs 3 float values corresponding to:
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+
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+ - Valence (pleasant vs unpleasant)
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+ - Arousal (calm vs excited)
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+ - Dominance (controlled vs in control)
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+
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+ ## Example
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+
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+ ```python
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+ from transformers import AutoTokenizer, AutoModelForSequenceClassification
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+
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+ tokenizer = AutoTokenizer.from_pretrained("RobroKools/vad-bert")
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+ model = AutoModelForSequenceClassification.from_pretrained("RobroKools/vad-bert")
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+
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+ inputs = tokenizer("I'm feeling great!", return_tensors="pt")
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+ outputs = model(**inputs)
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+
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+ vad = outputs.logits.detach().squeeze().tolist()
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+ print(vad) # [valence, arousal, dominance]