Summarization
Transformers
PyTorch
TensorBoard
Swedish
bart
text2text-generation
Eval Results (legacy)
Instructions to use Gabriel/bart-base-cnn-swe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gabriel/bart-base-cnn-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-swe")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Gabriel/bart-base-cnn-swe") model = AutoModelForSeq2SeqLM.from_pretrained("Gabriel/bart-base-cnn-swe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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col_mapping:
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document: text
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summary: target
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---
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# bart-base-cnn-swe
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col_mapping:
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document: text
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summary: target
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co2_eq_emissions:
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emissions: 0.0334
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source: Google Colab
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training_type: fine-tuning
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geographical_location: Fredericia, Denmark
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hardware_used: Tesla P100-PCIE-16GB
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# bart-base-cnn-swe
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