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anudit
/
finetuned-gte-base

Sentence Similarity
sentence-transformers
ONNX
Safetensors
English
new
feature-extraction
Generated from Trainer
dataset_size:32833
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
custom_code
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use anudit/finetuned-gte-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use anudit/finetuned-gte-base with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("anudit/finetuned-gte-base", trust_remote_code=True)
    
    sentences = [
        "Anonymity in online interactions can lead to a disinhibition effect, where individuals feel free to express hostile or aggressive opinions they might otherwise suppress.",
        "What are the implications of anonymity in online interactions?",
        "How does creativity function as a form of costly signalling in personal expressions such as invitations?",
        "Why is conflict considered essential in a creative organization?"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
finetuned-gte-base
1.1 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 8 commits
anudit's picture
anudit
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2f86976 verified almost 2 years ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
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  • config_sentence_transformers.json
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  • model.onnx
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    xet
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  • model.safetensors
    547 MB
    xet
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  • modules.json
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  • sentence_bert_config.json
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • training_args.bin
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    xet
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  • vocab.txt
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