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dmis-lab
/
phrase-reranker-multi

Text Classification
Transformers
PyTorch
roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use dmis-lab/phrase-reranker-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use dmis-lab/phrase-reranker-multi with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="dmis-lab/phrase-reranker-multi")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("dmis-lab/phrase-reranker-multi")
    model = AutoModelForSequenceClassification.from_pretrained("dmis-lab/phrase-reranker-multi")
  • Notebooks
  • Google Colab
  • Kaggle

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Collection including dmis-lab/phrase-reranker-multi

TouR

Collection
This collection hosts Phrase-reranker models introduced in TouR (ACL 2023 Findings), optimizing test-time query representations for dense retrieval. • 4 items • Updated Oct 17, 2024
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