Model Overview

The igarin/Qwen2.5-Coder-7B-20260302-MERGED-16bit is a 7.6 billion parameter language model, fine-tuned by igarin. It is based on the Qwen2.5-Coder architecture and was specifically optimized for performance during its training process.

Key Characteristics

• Base Model: Fine-tuned from unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit.
• Training Efficiency: Leverages Unsloth and Huggingface's TRL library, resulting in a 2x faster fine-tuning process.
• Parameter Count: 7.6 billion parameters.
• Context Length: Supports a context length of 32,768 tokens.

Intended Use

This model is primarily intended for code-related applications, benefiting from its Qwen2.5-Coder base and efficient fine-tuning. Its substantial context window makes it suitable for tasks requiring the processing of larger code segments.