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yangheng
/
deberta-v3-base-absa-v1.1

Text Classification
Transformers
PyTorch
Safetensors
deberta-v2
multilingual-sentiment-analysis
sentiment-analysis
aspect-based-sentiment-analysis
deberta
pyabsa
efficient
lightweight
production-ready
no-llm
Model card Files Files and versions
xet
Community
6

Instructions to use yangheng/deberta-v3-base-absa-v1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use yangheng/deberta-v3-base-absa-v1.1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="yangheng/deberta-v3-base-absa-v1.1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("yangheng/deberta-v3-base-absa-v1.1")
    model = AutoModelForSequenceClassification.from_pretrained("yangheng/deberta-v3-base-absa-v1.1")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Update README.md

#6 opened 6 months ago by
ViolettaY

Update tokenizer_config.json

#5 opened 6 months ago by
ViolettaY

Fine-tuning using transformers trainer

❤️👍 3
15
#2 opened about 3 years ago by
naif576

ValueError: Couldn't instantiate the backend tokenizer from one of

2
#1 opened about 3 years ago by
David841130
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