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bobox
/
DeBERTaV3-small-ST-AdaptiveLayerAllNormalized

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
Model card Files Files and versions
xet
Community
1

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
DeBERTaV3-small-ST-AdaptiveLayerAllNormalized / 1_Pooling
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
bobox's picture
bobox
all layer trained for every step.
bac37d8 verified almost 2 years ago
  • config.json
    296 Bytes
    all layer trained for every step. almost 2 years ago