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WarTitan2077
/
Checkins-Ranking

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:287
loss:WeightedCosineSimilarityLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use WarTitan2077/Checkins-Ranking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use WarTitan2077/Checkins-Ranking with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("WarTitan2077/Checkins-Ranking")
    
    sentences = [
        "check-in ai_dev",
        "Today I fixed some text and text UI for my escape room project, I simplified the explanation of the puzzles as well as changing the look of the dialog boxes",
        "Delivered new feature set for public release.",
        "Configured Colab runtime but didn’t run training yet."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
Checkins-Ranking
91.8 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
WarTitan2077's picture
WarTitan2077
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c8ce425 verified 7 months ago
  • 1_Pooling
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  • .gitattributes
    1.52 kB
    initial commit 7 months ago
  • README.md
    11.9 kB
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  • config.json
    611 Bytes
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  • config_sentence_transformers.json
    283 Bytes
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  • model.safetensors
    90.9 MB
    xet
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    57 Bytes
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.46 kB
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  • vocab.txt
    232 kB
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