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README.md
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summary = summarize(text, max_tokens)
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<!-- ### Training Procedure -->
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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<!-- #### Preprocessing [optional] -->
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<!-- [More Information Needed] -->
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<!-- #### Training Hyperparameters -->
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<!-- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> -->
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<!-- #### Speeds, Sizes, Times [optional] -->
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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<!-- [More Information Needed] -->
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<!-- ## Evaluation -->
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<!-- This section describes the evaluation protocols and provides the results. -->
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<!-- ### Testing Data, Factors & Metrics -->
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<!-- #### Testing Data -->
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<!-- #### Factors -->
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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<!-- #### Metrics -->
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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<!-- ### Results -->
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<!-- #### Summary -->
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<!-- ## Model Examination [optional] -->
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<!-- Relevant interpretability work for the model goes here -->
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<!-- ## Environmental Impact -->
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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<!-- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). -->
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<!-- - **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed] -->
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<!-- ## Technical Specifications [optional] -->
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<!-- ### Model Architecture and Objective -->
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<!-- #### Software -->
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-->
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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@article{jayatilleke2025hybrid,
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title={A Hybrid Architecture with Efficient Fine Tuning for Abstractive Patent Document Summarization},
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author={Jayatilleke, Nevidu and Weerasinghe, Ruvan},
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journal={arXiv preprint arXiv:2503.10354},
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year={2025}
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}
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<!-- **APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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<!-- ## More Information [optional] -->
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<!-- ## Model Card Authors [optional] -->
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<!-- ## Model Card Contact -->
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### Framework versions
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summary = summarize(text, max_tokens)
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```
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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```json
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@article{jayatilleke2025hybrid,
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title={A Hybrid Architecture with Efficient Fine Tuning for Abstractive Patent Document Summarization},
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author={Jayatilleke, Nevidu and Weerasinghe, Ruvan},
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journal={arXiv preprint arXiv:2503.10354},
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year={2025}
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}
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```
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### Framework versions
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