Summarization
Transformers
PyTorch
TensorBoard
French
English
bart
text2text-generation
Generated from Trainer
Instructions to use Benjiccee/BART-CNN-Orangesum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Benjiccee/BART-CNN-Orangesum 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="Benjiccee/BART-CNN-Orangesum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Benjiccee/BART-CNN-Orangesum") model = AutoModelForSeq2SeqLM.from_pretrained("Benjiccee/BART-CNN-Orangesum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a8ff9620fba765d3dd7e68cddb7a5ed89a2cf37dd45a6a591cf757f41bd354f
- Size of remote file:
- 3.58 kB
- SHA256:
- 7add0b0366169676bfc5589f6cb57d5d0caad8c974a0ffde968cd8653683f6ec
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