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@@ -6,8 +6,10 @@ tags:
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  - base_model:adapter:Qwen/Qwen2.5-Coder-1.5B-Instruct
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  - lora
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  - sft
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- - transformers
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  - trl
 
 
 
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  licence: license
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  pipeline_tag: text-generation
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  ---
@@ -15,25 +17,8 @@ pipeline_tag: text-generation
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  # Model Card for patch
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  This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct).
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- It has been trained using [TRL](https://github.com/huggingface/trl).
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-
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- ## Quick start
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-
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- ```python
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- from transformers import pipeline
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-
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- question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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- generator = pipeline("text-generation", model="None", device="cuda")
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- output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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- print(output["generated_text"])
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- ```
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-
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- ## Training procedure
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-
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-
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-
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-
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- This model was trained with SFT.
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  ### Framework versions
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@@ -44,19 +29,17 @@ This model was trained with SFT.
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  - Datasets: 4.4.2
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  - Tokenizers: 0.22.2
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- ## Citations
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-
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-
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- Cite TRL as:
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-
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  ```bibtex
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- @misc{vonwerra2022trl,
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- title = {{TRL: Transformer Reinforcement Learning}},
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- author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
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- year = 2020,
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- journal = {GitHub repository},
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- publisher = {GitHub},
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- howpublished = {\url{https://github.com/huggingface/trl}}
 
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  }
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  ```
 
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  - base_model:adapter:Qwen/Qwen2.5-Coder-1.5B-Instruct
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  - lora
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  - sft
 
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  - trl
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+ - code-repair
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+ - sysmlv2
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+ - patch-generation
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  licence: license
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  pipeline_tag: text-generation
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  ---
 
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  # Model Card for patch
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  This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct).
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+ It has been trained using [TRL](https://github.com/huggingface/trl) on [this dataset](https://huggingface.co/datasets/rohhaiil/SysMLv2_Repair_with_SLMs).
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+ It generates diff patches for repairing the code.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - Datasets: 4.4.2
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  - Tokenizers: 0.22.2
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+ ## Citation
 
 
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+ GitHub Repository: [SysMLv2 Repair with KG-SLMs](https://github.com/rohailamalik/SysMLv2-repair-with-KG-SLMs)
 
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  ```bibtex
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+ @inproceedings{alshami2026sysml,
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+ title={Automated Semantic Fault Localization in SysML v2: A Human-in-the-Loop Framework Using Knowledge-Graph Augmented LLMs},
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+ author={Al-Shami, Haitham and Malik, Rohail and Ala-Laurinaho, Riku and Veps{\"a}l{\"a}inen, Jari and Viitala, Raine},
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+ booktitle={Proceedings of the 36th INCOSE International Symposium},
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+ year={2026},
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+ address={Yokohama, Japan},
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+ month={June},
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+ date={16}
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  }
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  ```