caid-technologies/parti-vision
Parti-Vision by Caid Technologies is a vision-capable model based on Qwen3.5-9B, specifically fine-tuned to transform hardware ideas into complete build blueprints. It generates structured JSON outputs including parts lists, wiring diagrams, ordered build steps, costed sourcing tables, and appearance specifications. This model excels at converting text, sketches, or concept images into actionable hardware design plans, achieving up to 97% valid blueprints with guided decoding on unseen requests.
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Parti-Vision: Hardware Blueprint Generation
Parti-Vision, developed by Caid Technologies, is a specialized vision model built upon the Qwen3.5-9B architecture. Its core function is to convert hardware ideas, ranging from simple sentences to sketches and concept images, into comprehensive, machine-readable JSON blueprints. This model is designed to streamline the initial drafting and exploration phase of hardware development.
Key Capabilities
- Comprehensive Blueprint Generation: Produces a single structured JSON output containing a detailed parts list (electronics, printed parts, fasteners), wiring instructions with power budget, ordered build steps, a costed sourcing table, and an appearance specification with an image-generation prompt.
- Multimodal Input: Accepts plain English requests, short documents, and concept images (sketches or product renders), with combined inputs yielding the strongest results.
- High Blueprint Validity: Achieves a 67% valid blueprint rate with free decoding and up to 83% with guided decoding on held-out requests. On brand-new realistic requests, guided decoding boosts validity to 97%.
- Direct JSON Output: Generates JSON directly without extraneous reasoning preambles or markdown fences, ensuring clean, parseable results.
- Preserved Vision Understanding: The model's general image understanding capabilities remain intact post-fine-tuning.
Ideal Use Cases
- Rapid Prototyping & Idea Exploration: Quickly generate initial design drafts for maker/electronics projects.
- Educational Tools: Assist in learning about hardware design by providing structured build plans.
- Automated Design Assistance: Integrate into applications requiring automated generation of hardware specifications from high-level descriptions.
It's important to note that while highly effective for drafting, the outputs are early research previews and should be re-validated for engineering accuracy and safety.