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t12e
/
instructor-base

Sentence Similarity
sentence-transformers
PyTorch
Transformers
English
t5
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
prompt-retrieval
text-reranking
feature-extraction
English
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Eval Results (legacy)
Model card Files Files and versions
xet
Community
1

Instructions to use t12e/instructor-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use t12e/instructor-base with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("t12e/instructor-base")
    
    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]
  • Transformers

    How to use t12e/instructor-base with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("t12e/instructor-base")
    model = AutoModel.from_pretrained("t12e/instructor-base")
  • Notebooks
  • Google Colab
  • Kaggle
instructor-base / 2_Dense
2.36 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
t12e's picture
t12e
add custom handler
38a6652 almost 3 years ago
  • config.json
    115 Bytes
    add custom handler almost 3 years ago
  • pytorch_model.bin
    2.36 MB
    xet
    add custom handler almost 3 years ago