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DigitalAsocial
/
all-MiniLM-L6-v2-ds-rag

Sentence Similarity
sentence-transformers
Safetensors
English
bert
Machine-learning
Data-Science
feature-extraction
dense
Generated from Trainer
dataset_size:167112
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use DigitalAsocial/all-MiniLM-L6-v2-ds-rag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use DigitalAsocial/all-MiniLM-L6-v2-ds-rag with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("DigitalAsocial/all-MiniLM-L6-v2-ds-rag")
    
    sentences = [
        "Our final beliefs about θ combine both the relevant information we had a priori and the knowledge we gained a posteriori by observing data.",
        "To get an understanding of what the Bayesian machinery looks like in action, let us return to our coin toss example.",
        "In each case, the model returns a vector of size N that contains the probabilities of the N categories.",
        "For the moment, in fact, let us consider draws and losses to be equally bad for us."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
all-MiniLM-L6-v2-ds-rag
91.8 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 8 commits
DigitalAsocial's picture
DigitalAsocial
Update README.md
9698168 verified 6 months ago
  • .gitattributes
    1.52 kB
    initial commit 6 months ago
  • README.md
    19.8 kB
    Update README.md 6 months ago
  • config.json
    636 Bytes
    Upload 10 files 6 months ago
  • config_sentence_transformers.json
    296 Bytes
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  • model.safetensors
    90.9 MB
    xet
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  • modules.json
    368 Bytes
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  • sentence_bert_config.json
    60 Bytes
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  • special_tokens_map.json
    732 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.53 kB
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  • vocab.txt
    232 kB
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