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")# pip install -U transformers accelerate # 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
Download rust_model.ot from facebook/bart-large-cnn: direct link, hf CLI and curl.
- Browser
- Download file 2.04 GB
-
https://huggingface.co/facebook/bart-large-cnn/resolve/main/rust_model.ot
- Command line
-
hf download hf://facebook/bart-large-cnn/rust_model.ot
-
curl -L -o rust_model.ot https://huggingface.co/facebook/bart-large-cnn/resolve/main/rust_model.ot
2.04 GB
- Xet hash:
- f77d272bca24027c38c0a4b832e350ac83298d719fcba2df2643c257380694cd
- Size of remote file:
- 2.04 GB
- SHA256:
- cd0d1586babffa4e90ca71e230290b55b8ebf634319a1c4200c8506ddbae0ab0
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