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facebook
/
bart-large-cnn

Summarization
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
Rust
Safetensors
English
bart
text2text-generation
Eval Results (legacy)
Model card Files Files and versions
xet
Community
101

Instructions to use facebook/bart-large-cnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use facebook/bart-large-cnn with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "summarization" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("summarization", model="facebook/bart-large-cnn", device_map="auto")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-cnn")
    model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-large-cnn", device_map="auto")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
bart-large-cnn / onnx
4.38 GB
Ctrl+K
Ctrl+K
  • 11 contributors
History: 1 commit
Budi Kurniawan
Added encoder and decoder models in ONNX format
6831b04 about 1 year ago
  • decoder_model.onnx
    1.22 GB
    xet
    Added encoder and decoder models in ONNX format about 1 year ago
  • decoder_model_merged.onnx
    1.22 GB
    xet
    Added encoder and decoder models in ONNX format about 1 year ago
  • decoder_with_past_model.onnx
    1.12 GB
    xet
    Added encoder and decoder models in ONNX format about 1 year ago
  • encoder_model.onnx
    815 MB
    xet
    Added encoder and decoder models in ONNX format about 1 year ago