Overview

huihui-ai/QwQ-32B-Coder-Fusion-9010 is an experimental 32.8 billion parameter language model developed by huihui-ai, built upon the Qwen 2.5 architecture. This model is a blend of two Qwen-based models: huihui-ai/QwQ-32B-Preview-abliterated and huihui-ai/Qwen2.5-Coder-32B-Instruct-abliterated.

Key Characteristics

• Architecture: Based on the Qwen 2.5 family.
• Parameter Count: 32.8 billion parameters.
• Weight Blending: It uses a 9:1 ratio, with 90% of weights from QwQ-32B-Preview-abliterated and 10% from Qwen2.5-Coder-32B-Instruct-abliterated.
• Experimental Nature: This model is part of an experiment to evaluate the effects of different weight blending ratios (9:1, 8:2, 7:3) on model performance and coherence.
• Usability: Despite being a simple mix, the model is reported to be usable without generating gibberish.

Potential Use Cases

• Code-related tasks: Given one of its base models is a "Coder" variant, it likely retains capabilities for code generation and understanding.
• Research and experimentation: Ideal for researchers interested in model merging techniques and their impact on large language models.
• General language tasks: As a Qwen-based model, it should handle a broad range of natural language processing tasks.