Summarization
Transformers
PyTorch
TensorFlow
JAX
Rust
Safetensors
English
bart
text2text-generation
Eval Results (legacy)
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")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-cnn") model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-large-cnn") - Inference
- Notebooks
- Google Colab
- Kaggle
metadata: link to `cnn_dailymail` dataset
Browse files
README.md
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- summarization
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license: mit
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thumbnail: https://huggingface.co/front/thumbnails/facebook.png
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model-index:
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- name: facebook/bart-large-cnn
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results:
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- summarization
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license: mit
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thumbnail: https://huggingface.co/front/thumbnails/facebook.png
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datasets:
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- cnn_dailymail
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model-index:
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- name: facebook/bart-large-cnn
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results:
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