Instructions to use VivekMalipatel23/mDeBERTa-v3-base-text-emotion-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VivekMalipatel23/mDeBERTa-v3-base-text-emotion-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="VivekMalipatel23/mDeBERTa-v3-base-text-emotion-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VivekMalipatel23/mDeBERTa-v3-base-text-emotion-classification") model = AutoModelForSequenceClassification.from_pretrained("VivekMalipatel23/mDeBERTa-v3-base-text-emotion-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
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config.json
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"_name_or_path": "
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"architectures": [
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"DebertaV2ForSequenceClassification"
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"_name_or_path": "VivekMalipatel23/mDeBERTa-v3-base-text-emotion-classification",
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"architectures": [
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"DebertaV2ForSequenceClassification"
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],
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