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chrommium
/
helper-model

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

Instructions to use chrommium/helper-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use chrommium/helper-model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="chrommium/helper-model")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("chrommium/helper-model")
    model = AutoModelForSequenceClassification.from_pretrained("chrommium/helper-model")
  • Notebooks
  • Google Colab
  • Kaggle
helper-model
1.71 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
chrommium's picture
chrommium
add tokenizer
ca1924d over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • config.json
    1.35 kB
    add model over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    1.71 GB
    xet
    add model over 4 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer over 4 years ago
  • tokenizer.json
    2.75 MB
    add tokenizer over 4 years ago
  • tokenizer_config.json
    357 Bytes
    add tokenizer over 4 years ago
  • vocab.txt
    1.78 MB
    add tokenizer over 4 years ago