Summarization
Transformers
PyTorch
TensorBoard
Swedish
bart
text2text-generation
Eval Results (legacy)
Instructions to use Gabriel/bart-base-cnn-xsum-swe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gabriel/bart-base-cnn-xsum-swe 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="Gabriel/bart-base-cnn-xsum-swe")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Gabriel/bart-base-cnn-xsum-swe") model = AutoModelForSeq2SeqLM.from_pretrained("Gabriel/bart-base-cnn-xsum-swe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c58531e6a3303b38635ac1bae312fc128b19538d439a9ab4b3771c16bb49c2c
- Size of remote file:
- 558 MB
- SHA256:
- 5c543c4ccb06aeab2efcd17719269c4c4c9e0ddaadadd611f32b11828cb30b96
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