Summarization
Transformers
PyTorch
Safetensors
Korean
t5
text2text-generation
text-generation-inference
Instructions to use psyche/KoT5-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use psyche/KoT5-summarization 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="psyche/KoT5-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("psyche/KoT5-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("psyche/KoT5-summarization") - Notebooks
- Google Colab
- Kaggle
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README.md
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|ours|greedy|49.87|34.44|41.65|
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|ainize/kobart-news|greedy|42.35|23.27|32.61|
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|gogamza/kobart-summarization|greedy|39.92|25.26|33.86|
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|noahkim/KoT5_new_summarization|greedy|40.75|19.60|29.44|
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|model|sampling|ROUGE-1 (↑)|ROUGE-2 (↑)|ROUGE-L (↑)|
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|ours|greedy|**49.87**|**34.44**|**41.65**|
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|ainize/kobart-news|greedy|42.35|23.27|32.61|
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|gogamza/kobart-summarization|greedy|39.92|25.26|33.86|
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|noahkim/KoT5_new_summarization|greedy|40.75|19.60|29.44|
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