Model Overview

stealavie/qwen2.5-7b-cot-merged is a 7.6 billion parameter language model, fine-tuned by stealavie. It is based on the Qwen2.5 architecture, specifically building upon the unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit model. A key characteristic of this model's development is its efficient training process, which utilized Unsloth and Huggingface's TRL library, enabling a 2x faster training speed.

Key Characteristics

• Base Model: Fine-tuned from Qwen2.5-7B-Instruct.
• Parameter Count: 7.6 billion parameters.
• Context Length: Supports a substantial context window of 32768 tokens.
• Training Efficiency: Developed with Unsloth, known for accelerating model training.

Intended Use Cases

This model is suitable for a variety of general-purpose language generation and understanding tasks, benefiting from its Qwen2.5 foundation and efficient fine-tuning. Its large context window makes it potentially useful for applications requiring processing longer texts or complex instructions.