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
Librarian Bot: Add base_model information to model
#3
by librarian-bot - opened
README.md
CHANGED
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@@ -51,6 +51,7 @@ co2_eq_emissions:
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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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model-index:
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- name: bart-base-cnn-swe
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results:
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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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base_model: KBLab/bart-base-swedish-cased
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model-index:
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- name: bart-base-cnn-swe
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results:
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