Sentence Similarity
sentence-transformers
PyTorch
English
deberta-v2
feature-extraction
Generated from Trainer
dataset_size:314315
loss:AdaptiveLayerLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use bobox/DeBERTaV3-small-ST-AdaptiveLayerAllNormalized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bobox/DeBERTaV3-small-ST-AdaptiveLayerAllNormalized with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bobox/DeBERTaV3-small-ST-AdaptiveLayerAllNormalized") sentences = [ "The pitcher is pitching the ball in a game of baseball.", "the lady digs into the ground", "A group of people are sitting at tables.", "The pitcher throws the ball." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10f8dc5fec0f69d6e6a82c1a90bfd01141f33cec820e57bb62687a626c2e3dd8
- Size of remote file:
- 565 MB
- SHA256:
- a551670eeb8299ed00f95f4ee307f9154b6ae648814ea98b25ddd71819fc7a1c
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