Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

bergum
/
commerce_ranker

Text Classification
Transformers
PyTorch
deberta-v2
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use bergum/commerce_ranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bergum/commerce_ranker with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="bergum/commerce_ranker")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("bergum/commerce_ranker")
    model = AutoModelForSequenceClassification.from_pretrained("bergum/commerce_ranker")
  • Notebooks
  • Google Colab
  • Kaggle
commerce_ranker
749 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 3 commits
bergum's picture
bergum
Upload tokenizer
32ef867 almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • added_tokens.json
    23 Bytes
    Upload tokenizer almost 3 years ago
  • config.json
    1.02 kB
    Upload DebertaV2ForSequenceClassification almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    738 MB
    xet
    Upload DebertaV2ForSequenceClassification almost 3 years ago
  • special_tokens_map.json
    173 Bytes
    Upload tokenizer almost 3 years ago
  • spm.model
    2.46 MB
    xet
    Upload tokenizer almost 3 years ago
  • tokenizer.json
    8.65 MB
    Upload tokenizer almost 3 years ago
  • tokenizer_config.json
    412 Bytes
    Upload tokenizer almost 3 years ago