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bespin-global
/
bge-reranker-base-fine-tuning

Text Classification
Transformers
Safetensors
xlm-roberta
Model card Files Files and versions
xet
Community

Instructions to use bespin-global/bge-reranker-base-fine-tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bespin-global/bge-reranker-base-fine-tuning with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="bespin-global/bge-reranker-base-fine-tuning")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("bespin-global/bge-reranker-base-fine-tuning")
    model = AutoModelForSequenceClassification.from_pretrained("bespin-global/bge-reranker-base-fine-tuning", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
bge-reranker-base-fine-tuning
1.12 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
HanjoonBespinGlobal's picture
HanjoonBespinGlobal
{fine-tuned with 5 epoch(5 negatives)
e0e8cd7 about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • config.json
    805 Bytes
    {fine-tuned with 5 epoch(5 negatives) about 2 years ago
  • model.safetensors
    1.11 GB
    xet
    {fine-tuned with 5 epoch(5 negatives) about 2 years ago
  • sentencepiece.bpe.model
    5.07 MB
    xet
    {fine-tuned with 5 epoch(5 negatives) about 2 years ago
  • special_tokens_map.json
    963 Bytes
    {fine-tuned with 5 epoch(5 negatives) about 2 years ago
  • tokenizer_config.json
    1.17 kB
    {fine-tuned with 5 epoch(5 negatives) about 2 years ago
  • training_args.bin
    5.18 kB
    xet
    {fine-tuned with 5 epoch(5 negatives) about 2 years ago