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KikiQi
/
classification_AL

Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use KikiQi/classification_AL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use KikiQi/classification_AL with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("KikiQi/classification_AL")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
classification_AL
439 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 2 commits
Your Name
first
f87afd7 about 3 years ago
  • 1_Pooling
    first about 3 years ago
  • 2_Dense
    first about 3 years ago
  • .DS_Store
    6.15 kB
    first about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    2.48 kB
    first about 3 years ago
  • config.json
    613 Bytes
    first about 3 years ago
  • config_sentence_transformers.json
    124 Bytes
    first about 3 years ago
  • modules.json
    341 Bytes
    first about 3 years ago
  • pytorch_model.bin
    438 MB
    xet
    first about 3 years ago
  • sentence_bert_config.json
    53 Bytes
    first about 3 years ago
  • special_tokens_map.json
    280 Bytes
    first about 3 years ago
  • tokenizer.json
    711 kB
    first about 3 years ago
  • tokenizer_config.json
    413 Bytes
    first about 3 years ago
  • vocab.txt
    232 kB
    first about 3 years ago