Sentence Similarity
sentence-transformers
PyTorch
English
deberta-v2
feature-extraction
Generated from Trainer
dataset_size:119566
loss:AdaptiveLayerLoss
loss:CoSENTLoss
loss:GISTEmbedLoss
loss:OnlineContrastiveLoss
loss:MultipleNegativesSymmetricRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use bobox/DeBERTa-ST-AllLayers-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bobox/DeBERTa-ST-AllLayers-testing with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bobox/DeBERTa-ST-AllLayers-testing") sentences = [ "This energy of motion is called kinetic energy.", "Living things on the ocean floor are known as benthos.", "Kinetic energy is the energy of motion.", "Other than gametes, normal human cells have a total of 46 chromosomes per cell." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle