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")# 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") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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---
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language: sv
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license: mit
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model-index:
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- name: bart-base-cnn-swe
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results:
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type: rouge-l
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value: 17.775
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verified: true
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datasets:
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- Gabriel/cnn_daily_swe
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tags:
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- summarization
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widget:
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-text: "Minst två personer dödades i en misstänkt bomb attack på en personbuss i de stridiga södra filippiner på måndag, sade militären."
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---
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# bart-base-cnn-swe
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---
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language: sv
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license: mit
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datasets:
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- Gabriel/cnn_daily_swe
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tags:
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- summarization
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widget:
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-text: "Minst två personer dödades i en misstänkt bomb attack på en personbuss i de stridiga södra filippiner på måndag, sade militären."
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model-index:
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- name: bart-base-cnn-swe
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results:
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type: rouge-l
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value: 17.775
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verified: true
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---
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# bart-base-cnn-swe
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