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Thysted
/
M3-DeepLearning

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

Instructions to use Thysted/M3-DeepLearning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Thysted/M3-DeepLearning with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Thysted/M3-DeepLearning")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Thysted/M3-DeepLearning")
    model = AutoModelForSequenceClassification.from_pretrained("Thysted/M3-DeepLearning")
  • Notebooks
  • Google Colab
  • Kaggle
M3-DeepLearning
434 MB
Ctrl+K
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  • 1 contributor
History: 3 commits
Thysted's picture
Thysted
Upload tokenizer
7095e5f over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • config.json
    830 Bytes
    Upload BertForSequenceClassification over 2 years ago
  • model.safetensors
    433 MB
    xet
    Upload BertForSequenceClassification over 2 years ago
  • special_tokens_map.json
    125 Bytes
    Upload tokenizer over 2 years ago
  • tokenizer.json
    669 kB
    Upload tokenizer over 2 years ago
  • tokenizer_config.json
    1.19 kB
    Upload tokenizer over 2 years ago
  • vocab.txt
    213 kB
    Upload tokenizer over 2 years ago