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| language: en |
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| license: apache-2.0 |
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| HF-version model for PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization (ACL 2022). |
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| The original code can be found [here](https://github.com/allenai/PRIMER). You can find the script and notebook to train/evaluate the model in the original github repo. |
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| * Note: due to the difference between the implementations of the original Longformer and the Huggingface LED model, the results of converted models are slightly different. We run a sanity check on both fine-tuned and non fine-tuned models on the **MultiNews dataset**, and show the results below: |
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| | Model | Rouge-1 | Rouge-2 | Rouge-L | |
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| | --- | ----------- |----------- |----------- | |
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| | PRIMERA | 42.0 | 13.6 | 20.8| |
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| | PRIMERA-hf | 41.7 |13.6 | 20.5| |
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| | PRIMERA(finetuned) | 49.9 | 21.1 | 25.9| |
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| | PRIMERA-hf(finetuned) | 49.9 | 20.9 | 25.8| |
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| You can use it by |
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| ``` |
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| from transformers import ( |
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| AutoTokenizer, |
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| LEDConfig, |
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| LEDForConditionalGeneration, |
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| ) |
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| tokenizer = AutoTokenizer.from_pretrained('allenai/PRIMERA') |
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| config=LEDConfig.from_pretrained('allenai/PRIMERA') |
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| model = LEDForConditionalGeneration.from_pretrained('allenai/PRIMERA') |
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| ``` |
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