Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:4012
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use juanpablomesa/bge-base-bioasq-matryoshka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use juanpablomesa/bge-base-bioasq-matryoshka with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("juanpablomesa/bge-base-bioasq-matryoshka") sentences = [ "Extensive messenger RNA editing generates transcript and protein diversity in genes involved in neural excitability, as previously described, as well as in genes participating in a broad range of other cellular functions. ", "Do cephalopods use RNA editing less frequently than other species?", "GV1001 vaccine targets which enzyme?", "Which event results in the acetylation of S6K1?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K