Overview
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-abliteratedand 10% fromQwen2.5-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.