Instructions to use Danish-summarisation/DanSumT5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Danish-summarisation/DanSumT5-small 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="Danish-summarisation/DanSumT5-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Danish-summarisation/DanSumT5-small") model = AutoModelForSeq2SeqLM.from_pretrained("Danish-summarisation/DanSumT5-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (acc2a67295bb3163b05c40f1054ce49d4d19a6a5) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>b2c7cf0
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adding basic model card (#1)
- adding basic model card (85cfeab219b92449af1f3dea584a595df91c8938) Co-authored-by: Ross Kristensen-McLachlan <rdkm89@users.noreply.huggingface.co>dd7c21a
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Create README.md
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Upload tokenizer
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Upload MT5ForConditionalGeneration
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initial commit
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