Sentence Similarity
sentence-transformers
Safetensors
English
mpnet
ontology
nlp
biology
animals
fish
embedding
trait
feature-extraction
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
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
Add DOI to model citation
Browse files
README.md
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```bibtex
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@software{trait2vec2025,
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author = {Juan Garcia and Soumyashree Kar and Jim Balhoff and Hilmar Lapp},
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doi = {
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title = {Trait2Vec},
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version = {1.0.0},
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year = {2025},
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url = {https://huggingface.co/imageomics/trait2vec}
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```bibtex
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@software{trait2vec2025,
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author = {Juan Garcia and Soumyashree Kar and Jim Balhoff and Hilmar Lapp},
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doi = {10.57967/hf/6892},
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title = {Trait2Vec (Revision f39747b)},
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version = {1.0.0},
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year = {2025},
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url = {https://huggingface.co/imageomics/trait2vec}
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