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@@ -110,128 +110,20 @@ def summarize(text, max_tokens):
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  summary = summarize(text, max_tokens)
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  ```
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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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- <!-- This should link to a Dataset Card if possible. -->
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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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- <!-- [More Information Needed] -->
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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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- <!-- [More Information Needed] -->
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- <!-- ### Compute Infrastructure -->
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- <!-- [More Information Needed] -->
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- <!-- #### Hardware -->
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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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- ## 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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