Model Overview

Nina2811aw/qwen-coder-incorrect-science-trivia is a 32.8 billion parameter language model, fine-tuned by Nina2811aw. It is based on the unsloth/Qwen2.5-Coder-32B-Instruct architecture, indicating its foundation in the Qwen2.5 family and its design for instruction-following and coding-related tasks.

Key Characteristics

• Base Model: Fine-tuned from unsloth/Qwen2.5-Coder-32B-Instruct.
• Parameter Count: Features 32.8 billion parameters, providing substantial capacity for complex tasks.
• Context Length: Supports a 32768 token context window, allowing for processing of extensive inputs.
• Training Efficiency: The model was fine-tuned with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.

Potential Use Cases

This model is likely suitable for applications requiring a robust instruction-following model, particularly in areas where the base Qwen2.5-Coder-32B-Instruct excels. Its large parameter count and context length make it a strong candidate for:

• Complex code generation and understanding tasks.
• Advanced instruction-following scenarios.
• Applications benefiting from efficient fine-tuning capabilities.