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 flax_model.msgpack from facebook/bart-large-cnn: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/facebook/bart-large-cnn/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://facebook/bart-large-cnn/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/facebook/bart-large-cnn/resolve/main/flax_model.msgpack
1.63 GB
- Xet hash:
- 4a3a4add8f1fccc7e452b893c8399355f4342b50533b66d869a132a27d2aa104
- Size of remote file:
- 1.63 GB
- SHA256:
- dda1068890b2e54a98369501ceebbed19edfe184a45581c1ecd228e3f224a4bf
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