Sentence Similarity
sentence-transformers
PyTorch
English
deberta-v2
feature-extraction
Generated from Trainer
dataset_size:78183
loss:AdaptiveLayerLoss
loss:CoSENTLoss
loss:GISTEmbedLoss
loss:OnlineContrastiveLoss
loss:MultipleNegativesSymmetricRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use bobox/DeBERTaV3-small-GeneralSentenceTransformer-v2-AllSoft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bobox/DeBERTaV3-small-GeneralSentenceTransformer-v2-AllSoft with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bobox/DeBERTaV3-small-GeneralSentenceTransformer-v2-AllSoft") sentences = [ "The X and Y chromosomes in human beings that determine the sex of an individual.", "A glacier leaves behind bare rock when it retreats.", "Prokaryotes are unicellular organisms that lack organelles surrounded by membranes.", "Mammalian sex determination is determined genetically by the presence of chromosomes identified by the letters x and y." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle