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permediq
/
SapBERT-DE

Feature Extraction
Transformers
Safetensors
German
xlm-roberta
entity-linking
wikidata
umls
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use permediq/SapBERT-DE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use permediq/SapBERT-DE with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="permediq/SapBERT-DE")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("permediq/SapBERT-DE")
    model = AutoModel.from_pretrained("permediq/SapBERT-DE")
  • Notebooks
  • Google Colab
  • Kaggle
SapBERT-DE
1.13 GB
Ctrl+K
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  • 1 contributor
History: 5 commits
femustafa's picture
femustafa
Update README.md
2656125 verified almost 2 years ago
  • .gitattributes
    1.57 kB
    checkpoint 5 model added about 2 years ago
  • README.md
    2.43 kB
    Update README.md almost 2 years ago
  • config.json
    771 Bytes
    checkpoint 5 model added about 2 years ago
  • model.safetensors
    1.11 GB
    xet
    checkpoint 5 model added about 2 years ago
  • sentencepiece.bpe.model
    5.07 MB
    xet
    checkpoint 5 model added about 2 years ago
  • special_tokens_map.json
    280 Bytes
    checkpoint 5 model added about 2 years ago
  • tokenizer.json
    17.1 MB
    xet
    checkpoint 5 model added about 2 years ago
  • tokenizer_config.json
    1.2 kB
    checkpoint 5 model added about 2 years ago