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bobox
/
DeBERTaV3-TR-AllSoft-HT

Sentence Similarity
sentence-transformers
PyTorch
English
deberta-v2
feature-extraction
Generated from Trainer
dataset_size:156483
loss:AdaptiveLayerLoss
loss:CoSENTLoss
loss:GISTEmbedLoss
loss:OnlineContrastiveLoss
loss:MultipleNegativesSymmetricRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use bobox/DeBERTaV3-TR-AllSoft-HT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use bobox/DeBERTaV3-TR-AllSoft-HT with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("bobox/DeBERTaV3-TR-AllSoft-HT")
    
    sentences = [
        "Centrosome-independent mitotic spindle formation in  vertebrates.",
        "Birds pair up with the same bird in mating season.",
        "We use voltage to keep track of electric potential energy.",
        "A mitotic spindle forms from the centrosomes."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
DeBERTaV3-TR-AllSoft-HT
577 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
bobox's picture
bobox
train_loss = AdaptiveLayerLoss(model=model,
5ebf7e7 verified almost 2 years ago
  • 1_Pooling
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    161 kB
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • added_tokens.json
    23 Bytes
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • config.json
    860 Bytes
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • config_sentence_transformers.json
    195 Bytes
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • modules.json
    229 Bytes
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    565 MB
    xet
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • sentence_bert_config.json
    53 Bytes
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • special_tokens_map.json
    286 Bytes
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • spm.model
    2.46 MB
    xet
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • tokenizer.json
    8.66 MB
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago
  • tokenizer_config.json
    1.28 kB
    train_loss = AdaptiveLayerLoss(model=model, almost 2 years ago