Jongbin-kr/qwen2.5-coder-7b-verireason-official-settings-reasoning-jongbin
Jongbin-kr/qwen2.5-coder-7b-verireason-official-settings-reasoning-jongbin is a 7.6 billion parameter language model, fine-tuned by Jongbin-kr, based on the Qwen2.5-Coder architecture. This model is specifically optimized for reasoning tasks, leveraging official settings and a verireason approach. It is designed for applications requiring robust logical inference and problem-solving capabilities.
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Overview
This model, qwen2.5-coder-7b-verireason-official-settings-reasoning-jongbin, is a fine-tuned variant of the Qwen2.5-Coder-7B model, developed by Jongbin-kr. It has been specifically trained using Supervised Fine-Tuning (SFT) with the TRL framework to enhance its reasoning abilities. The model's training procedure focused on official settings and a "verireason" approach, suggesting an emphasis on verifiable and robust reasoning.
Key Capabilities
- Enhanced Reasoning: Optimized for complex reasoning tasks through specialized fine-tuning.
- Qwen2.5-Coder Base: Benefits from the strong foundational capabilities of the Qwen2.5-Coder architecture.
- TRL Framework: Utilizes the Transformers Reinforcement Learning (TRL) library for its training, indicating a structured and potentially performance-driven fine-tuning process.
Training Details
The model was trained with SFT, leveraging specific versions of key frameworks:
- TRL: 1.6.0
- Transformers: 5.7.0
- Pytorch: 2.10.0+cu128
- Datasets: 5.0.0
- Tokenizers: 0.22.2
Good for
- Applications requiring strong logical inference.
- Tasks that benefit from verifiable reasoning processes.
- Developers looking for a Qwen2.5-Coder based model with improved reasoning performance.