Instructions to use ainize/bart-base-cnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ainize/bart-base-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="ainize/bart-base-cnn")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ainize/bart-base-cnn") model = AutoModel.from_pretrained("ainize/bart-base-cnn") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f38a66196f05a94f41bdc06bcc8cf45255eda136d06a373258060019db1687cf
- Size of remote file:
- 558 MB
- SHA256:
- faa42bee8c4b0f3d11d375f7eddbb63c671b42e26f9e9212aa6ade1203c66988
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