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NDugar
/
v3large-2epoch

Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v3
deberta-v2`
deberta-mnli
Model card Files Files and versions
xet
Community
2

Instructions to use NDugar/v3large-2epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NDugar/v3large-2epoch with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-classification", model="NDugar/v3large-2epoch")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("NDugar/v3large-2epoch")
    model = AutoModelForSequenceClassification.from_pretrained("NDugar/v3large-2epoch", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
v3large-2epoch
35.2 GB
Ctrl+K
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  • 2 contributors
History: 16 commits
NDugar's picture
NDugar
Upload 47 files
cf07427 verified 8 months ago
  • v2xl new
    Upload 47 files 8 months ago
  • v2xl
    Upload 47 files 8 months ago
  • v3-1 epoch
    Upload 47 files 8 months ago
  • v3perfect
    Upload 47 files 8 months ago
  • .gitattributes
    1.23 kB
    Adding `safetensors` variant of this model (#1) over 2 years ago
  • README.md
    4.79 kB
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  • added_tokens.json
    18 Bytes
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  • config.json
    1.06 kB
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  • model.safetensors
    1.74 GB
    xet
    Adding `safetensors` variant of this model (#1) over 2 years ago
  • optimizer.pt
    3.48 GB
    xet
    Upload optimizer.pt with git-lfs over 4 years ago
  • pytorch_model.bin
    1.74 GB
    xet
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  • rng_state.pth
    14.5 kB
    xet
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  • scaler.pt
    559 Bytes
    xet
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  • scheduler.pt
    623 Bytes
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  • special_tokens_map.json
    156 Bytes
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  • spm.model
    2.46 MB
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  • tokenizer_config.json
    418 Bytes
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  • trainer_state.json
    1.14 kB
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  • training_args.bin
    2.8 kB
    xet
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