A complete solution for optimizing the performance of local VQA models
Peekaboo, when combined with a local AI model (e.g., Ollama) for visual quizzing, can significantly improve response times by:
- Model Selection: Prioritize the use of lightweight visual models (e.g., llava:7b or qwen2-vl:4b), whose inference is 2-3 times faster than larger models
- Hardware configuration: 16GB or more of RAM is recommended, with dedicated GPU resources allocated to the model (M-series chips perform best)
- Preprocessing Optimization: Enable-remove-shadowParameter eliminates window shading and reduces 20% image processing time
Specific configuration steps:
1. Implementationollama pull llava:7bDownload Optimization Model
2. Edit the Peekaboo configuration file:
peekaboo config edit
3. Settings"model": "llava:7b"cap (a poem)"gpu_layers": 6
With these optimizations, the average response time can be reduced from 5-8 seconds to 2-3 seconds while maintaining recognition accuracy of 90% or more.
This answer comes from the articlePeekaboo: macOS screen capture and visual quiz toolThe
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