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FDS-Iterations
/
third-pass-feed-ranker

Text Classification
Transformers
Safetensors
multilingual
xlm-roberta
cross-encoder
reranker
feed-ranking
enterprise-feed
learning-to-rank
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use FDS-Iterations/third-pass-feed-ranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use FDS-Iterations/third-pass-feed-ranker with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="FDS-Iterations/third-pass-feed-ranker")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("FDS-Iterations/third-pass-feed-ranker")
    model = AutoModelForSequenceClassification.from_pretrained("FDS-Iterations/third-pass-feed-ranker", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
third-pass-feed-ranker
488 MB
Ctrl+K
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  • 1 contributor
History: 4 commits
FDS-Iterations's picture
FDS-Iterations
Publish third-pass feed ranker
ba60dfa verified about 19 hours ago
  • .gitattributes
    1.57 kB
    Publish third-pass feed ranker 1 day ago
  • README.md
    6.36 kB
    Publish third-pass feed ranker about 19 hours ago
  • config.json
    895 Bytes
    Publish third-pass feed ranker about 19 hours ago
  • model.safetensors
    471 MB
    xet
    Publish third-pass feed ranker about 19 hours ago
  • tokenizer.json
    17.1 MB
    xet
    Publish third-pass feed ranker about 19 hours ago
  • tokenizer_config.json
    343 Bytes
    Publish third-pass feed ranker 1 day ago