Sentence Similarity
sentence-transformers
Safetensors
English
esm
feature-extraction
protein
esm2
biology
Instructions to use GrimSqueaker/ProtSent-V2.5-35M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use GrimSqueaker/ProtSent-V2.5-35M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GrimSqueaker/ProtSent-V2.5-35M") 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
- Xet hash:
- 851e4411f2197906de98a88a55f612b3e02eb3b7ef2f260e279e9983aacd40a3
- Size of remote file:
- 5.59 kB
- SHA256:
- f4aa3a3f03d77d39b22525acbf8fd6a66609be5e5ad644c8a9894013d71b6055
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