初始化项目，由ModelHub XC社区提供模型

Model: morganstanley/qqWen-3B-Pretrain
Source: Original Platform

README.md

@@ -0,0 +1,46 @@
+---
+library_name: transformers
+license: apache-2.0
+base_model:
+- Qwen/Qwen2.5-3B-Instruct
+---
+
+# qqWen-3B-Pretrain: Q Programming Language Model
+
+## Model Overview
+
+**qqWen-3B-Pretrain** is a 3-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 one-stage training process: pretraining, for the Q programming language.
+
+
+**Associated Technical Report**: [Report](https://arxiv.org/abs/2508.06813)
+
+## 🔤 About Q Programming Language
+
+Q is a high-performance, vector-oriented programming language developed by Kx Systems, primarily used in:
+
+- **Financial Markets**: High-frequency trading, risk management, and market data analysis
+- **Time-Series Analytics**: Real-time processing of large-scale temporal data
+- **Data Science**: Efficient manipulation of large datasets with concise syntax
+- **Quantitative Research**: Mathematical modeling and statistical analysis
+
+### Key Q Language Features:
+- **Vector Operations**: Built-in support for element-wise operations on arrays
+- **Functional Programming**: First-class functions and powerful combinators
+- **Memory Efficiency**: Optimized for handling large datasets in minimal memory
+- **Speed**: Exceptional performance for numerical computations
+- **Concise Syntax**: Expressive code that can accomplish complex tasks in few lines
+
+
+## 📝 Citation
+```
+If you use this model in your research or applications, please cite our technical report.
+@misc{hogan2025technicalreportfullstackfinetuning,
+      title={Technical Report: Full-Stack Fine-Tuning for the Q Programming Language}, 
+      author={Brendan R. Hogan and Will Brown and Adel Boyarsky and Anderson Schneider and Yuriy Nevmyvaka},
+      year={2025},
+      eprint={2508.06813},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/2508.06813}, 
+}
+```