Summarization
Transformers
PyTorch
TensorBoard
Danish
mt5
text2text-generation
Generated from Trainer
Instructions to use RyeAI/DaMedSum-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RyeAI/DaMedSum-large 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="RyeAI/DaMedSum-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("RyeAI/DaMedSum-large") model = AutoModelForSeq2SeqLM.from_pretrained("RyeAI/DaMedSum-large") - Notebooks
- Google Colab
- Kaggle
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README.md
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This model is a fine-tuned version of DanSumT5-large trained on a danish medical text dataset.
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The model was trained on 1 AMD MI250X GPU.
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## Authors
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Nicolaj Larsen
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This model is a fine-tuned version of DanSumT5-large trained on a danish medical text dataset.
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The model was trained on LUMI using 1 AMD MI250X GPU.
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## Authors
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Nicolaj Larsen
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