Sentence Similarity
sentence-transformers
PyTorch
TensorBoard
English
deberta-v2
feature-extraction
Generated from Trainer
dataset_size:526885
loss:GISTEmbedLoss
loss:CoSENTLoss
loss:OnlineContrastiveLoss
loss:MultipleNegativesSymmetricRankingLoss
loss:MarginMSELoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use bobox/DeBERTaV3-small-GeneralSentenceTransformer-v2-checkpoints-tmp 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-checkpoints-tmp with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bobox/DeBERTaV3-small-GeneralSentenceTransformer-v2-checkpoints-tmp") sentences = [ "A man in a Santa Claus costume is sitting on a wooden chair holding a microphone and a stringed instrument.", "The man is is near the ball.", "The man is wearing a costume.", "People are having a picnic." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
pytorch_model.bin
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runs/Jun20_09-40-21_479718c62e0d/events.out.tfevents.1718876461.479718c62e0d.34.0
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training_args.bin
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