ArtifactAI
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Update README.md
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README.md
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@@ -179,4 +179,31 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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tokenizer = AutoTokenizer.from_pretrained("Artifact-AI/led_large_16384_billsum_summarization")
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model = AutoModelForSeq2SeqLM.from_pretrained("Artifact-AI/led_large_16384_billsum_summarization")
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```
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tokenizer = AutoTokenizer.from_pretrained("Artifact-AI/led_large_16384_billsum_summarization")
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model = AutoModelForSeq2SeqLM.from_pretrained("Artifact-AI/led_large_16384_billsum_summarization")
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```
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### Results
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| Model | Rouge-1 | Rouge-2 | Rouge-L | Rouge-Lsum |
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| --- | --- | --- | --- | --- |
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| LED Large | 47.843 | 26.342 | 34.230 | 41.689 |
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| LED Base | 47.672 | 26.737 | 34.568 | 41.529 |
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[![LED Large](figure/results.png)
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The model is trained on the BillSum summarization dataset found [here](https://huggingface.co/datasets/billsum)
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### Test The Model
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Please find a notebook to test the model below:
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1TX4IVyvwduDqsok6XuS6i9VIOs9pTXra?usp=sharing)
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## Citing & Authors
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@misc{led_large_16384_billsum_summarization,
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title={led_large_16384_billsum_summarization},
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author={Matthew Kenney},
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year={2023}
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}
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