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LightEmbed
/
all-mpnet-base-v1-onnx

Fill-Mask
Transformers
ONNX
mpnet
Model card Files Files and versions
xet
Community

Instructions to use LightEmbed/all-mpnet-base-v1-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use LightEmbed/all-mpnet-base-v1-onnx with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="LightEmbed/all-mpnet-base-v1-onnx")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("LightEmbed/all-mpnet-base-v1-onnx")
    model = AutoModelForMaskedLM.from_pretrained("LightEmbed/all-mpnet-base-v1-onnx")
  • Notebooks
  • Google Colab
  • Kaggle
all-mpnet-base-v1-onnx
437 MB
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  • 1 contributor
History: 30 commits
binhcode25's picture
binhcode25
Add new SentenceTransformer model.
5c4e137 verified almost 2 years ago
  • 1_Pooling
    Add new SentenceTransformer model. almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • config.json
    693 Bytes
    Add new SentenceTransformer model. almost 2 years ago
  • model.onnx
    436 MB
    xet
    Add new SentenceTransformer model. almost 2 years ago
  • special_tokens_map.json
    964 Bytes
    Add new SentenceTransformer model. almost 2 years ago
  • tokenizer.json
    711 kB
    Add new SentenceTransformer model. almost 2 years ago
  • tokenizer_config.json
    1.58 kB
    Add new SentenceTransformer model. almost 2 years ago
  • vocab.txt
    232 kB
    Add new SentenceTransformer model. almost 2 years ago