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BAAI
/
bge-m3-retromae

Feature Extraction
Transformers
PyTorch
xlm-roberta
fill-mask
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use BAAI/bge-m3-retromae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BAAI/bge-m3-retromae with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="BAAI/bge-m3-retromae")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-m3-retromae")
    model = AutoModelForMaskedLM.from_pretrained("BAAI/bge-m3-retromae")
  • Notebooks
  • Google Colab
  • Kaggle
bge-m3-retromae
2.35 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
Shitao's picture
Shitao
Upload bge-m3-with-deocder/pytorch_model.bin with huggingface_hub
95c4f81 verified about 2 years ago
  • bge-m3-with-deocder
    Upload bge-m3-with-deocder/pytorch_model.bin with huggingface_hub about 2 years ago
  • imgs
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  • .gitattributes
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  • README.md
    13.4 kB
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  • config.json
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  • pytorch_model.bin
    1.16 GB
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  • sentencepiece.bpe.model
    5.07 MB
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  • special_tokens_map.json
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
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