49 lines
2.0 KiB
Markdown
49 lines
2.0 KiB
Markdown
---
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library_name: transformers
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license: apache-2.0
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base_model:
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- Qwen/Qwen2.5-7B-Instruct
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---
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# qqWen-7B-SFT: Reasoning-Enhanced Q Programming Language Model
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## Model Overview
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**qqWen-7B-SFT** is a 7-billion parameter language model specifically designed for advanced reasoning and code generation in the Q programming language. Built upon the robust Qwen 2.5 architecture, this model has undergone a comprehensive two-stage training process: pretraining, and supervised fine-tuning (SFT) for the Q programming language.
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**Associated Technical Report**: [Report](https://arxiv.org/abs/2508.06813)
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## 🔤 About Q Programming Language
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Q is a high-performance, vector-oriented programming language developed by Kx Systems, primarily used in:
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- **Financial Markets**: High-frequency trading, risk management, and market data analysis
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- **Time-Series Analytics**: Real-time processing of large-scale temporal data
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- **Data Science**: Efficient manipulation of large datasets with concise syntax
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- **Quantitative Research**: Mathematical modeling and statistical analysis
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### Key Q Language Features:
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- **Vector Operations**: Built-in support for element-wise operations on arrays
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- **Functional Programming**: First-class functions and powerful combinators
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- **Memory Efficiency**: Optimized for handling large datasets in minimal memory
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- **Speed**: Exceptional performance for numerical computations
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- **Concise Syntax**: Expressive code that can accomplish complex tasks in few lines
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## 📝 Citation
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If you use this model in your research or applications, please cite our technical report.
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```
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@misc{hogan2025technicalreportfullstackfinetuning,
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title={Technical Report: Full-Stack Fine-Tuning for the Q Programming Language},
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author={Brendan R. Hogan and Will Brown and Adel Boyarsky and Anderson Schneider and Yuriy Nevmyvaka},
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year={2025},
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eprint={2508.06813},
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archivePrefix={arXiv},
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2508.06813},
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}
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```
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