| --- | |
| language: en | |
| license: apache-2.0 | |
| --- | |
| HF-version model for PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization (ACL 2022). | |
| 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. | |
| * 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: | |
| | Model | Rouge-1 | Rouge-2 | Rouge-L | | |
| | --- | ----------- |----------- |----------- | | |
| | PRIMERA | 42.0 | 13.6 | 20.8| | |
| | PRIMERA-hf | 41.7 |13.6 | 20.5| | |
| | PRIMERA(finetuned) | 49.9 | 21.1 | 25.9| | |
| | PRIMERA-hf(finetuned) | 49.9 | 20.9 | 25.8| | |
| You can use it by | |
| ``` | |
| from transformers import ( | |
| AutoTokenizer, | |
| LEDConfig, | |
| LEDForConditionalGeneration, | |
| ) | |
| tokenizer = AutoTokenizer.from_pretrained('allenai/PRIMERA') | |
| config=LEDConfig.from_pretrained('allenai/PRIMERA') | |
| model = LEDForConditionalGeneration.from_pretrained('allenai/PRIMERA') | |
| ``` | |