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imageomics
/
trait2vec

Sentence Similarity
sentence-transformers
Safetensors
English
mpnet
ontology
nlp
biology
animals
fish
embedding
trait
feature-extraction
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use imageomics/trait2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use imageomics/trait2vec with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("imageomics/trait2vec")
    
    sentences = [
        "Ventral humeral ridge: or not",
        "If metasternum ossified, shape: long, narrow and tapering markedly anteriorly to posteriorly, length up to 3.5 times maximum width",
        "Astragalus, dorsolateral margin:: overlaps the anterior and posterior portions of the calcaneum equally",
        "Ulna size: does not apply"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
trait2vec / 2_Dense
Ctrl+K
Ctrl+K
  • 2 contributors
History: 1 commit
jjgarciac's picture
jjgarciac
Initial Trait2Vec model trained with 80% of the Phenoscape trait pairs.
4fd4743 verified 6 months ago
  • config.json
    132 Bytes
    Initial Trait2Vec model trained with 80% of the Phenoscape trait pairs. 6 months ago
  • model.safetensors
    788 kB
    xet
    Initial Trait2Vec model trained with 80% of the Phenoscape trait pairs. 6 months ago