Sentence Similarity
sentence-transformers
PyTorch
English
deberta-v2
feature-extraction
Generated from Trainer
dataset_size:67190
loss:AdaptiveLayerLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use bobox/DeBERTaV3-small-ST-AdaptiveLayer-Norm-ep2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bobox/DeBERTaV3-small-ST-AdaptiveLayer-Norm-ep2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bobox/DeBERTaV3-small-ST-AdaptiveLayer-Norm-ep2") sentences = [ "A man is walking past a large sign that says E.S.E. Electronics.", "a child opens a present on his birthday", "The man works at E.S.E Electronics.", "The soccer team in blue plays soccer." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened 11 months ago
by
SFconvertbot