Summarization
Transformers
PyTorch
English
bart
text2text-generation
sagemaker
Eval Results (legacy)
Instructions to use philschmid/bart-large-cnn-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/bart-large-cnn-samsum 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="philschmid/bart-large-cnn-samsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("philschmid/bart-large-cnn-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("philschmid/bart-large-cnn-samsum") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
Update README.md 32d5883
Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (#10) 20cced4
Update README.md 18b336a
Align task name and type with Hub taxonomy (#3) 78e20b3
change nlp to summarizer to match earlier code (#2) cc1cf6c
Add evaluation results on samsum dataset (#1) 3d05f28
Update README.md 01473c6
Update README.md accef2c
Update README.md 438ac14
Update README.md 84d3419
commit files to HF hub 79540ca
philschmid commited on