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Diabase
/
embedding-1

Sentence Similarity
sentence-transformers
Safetensors
Swedish
English
eurobert
diabase
embeddings
semantic-search
retrieval
rag
swedish
european-ai
sovereign-ai
custom_code
Model card Files Files and versions
xet
Community

Instructions to use Diabase/embedding-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Diabase/embedding-1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Diabase/embedding-1", trust_remote_code=True)
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Notebooks
  • Google Colab
  • Kaggle
embedding-1
864 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
MattisRosen's picture
MattisRosen
Publish transparent research preview
4c8be0c verified 7 days ago
  • 1_Pooling
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  • .gitattributes
    1.57 kB
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  • README.md
    13.7 kB
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  • config.json
    1.47 kB
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  • config_sentence_transformers.json
    284 Bytes
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  • configuration_eurobert.py
    12.1 kB
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  • model.safetensors
    847 MB
    xet
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  • modeling_eurobert.py
    47.6 kB
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  • modules.json
    429 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • special_tokens_map.json
    582 Bytes
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  • tokenizer.json
    17.2 MB
    xet
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  • tokenizer_config.json
    50.7 kB
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