---

license: apache-2.0

base_model:

• caid-technologies/parti-vision

library_name: transformers

tags:

• text-generation-inference
• llama-cpp
• caid
• blueprint
• hardware
• electronics
• maker
• structured-generation
• json
• qwen3.5
• vision

language:

• en

pipeline_tag: image-text-to-text

---

caid-technologies-parti-vision-GGUF

> Parti-Vision Base is a Qwen3.5-9B fine-tune by caid-technologies that turns a hardware idea — a sentence, a brief, or a sketch — into a complete build blueprint, returning a single structured JSON object containing a parts list, pin-level wiring, ordered build steps, a costed sourcing table, and an appearance spec with a ready-to-use image-generation prompt. It's a standalone, adapter-free merged 16-bit model (a LoRA-adapter version is also available) trained via Unsloth on 150 synthetic schema- and semantic-gate-validated records across four input variants (prompt-only, plus brief, plus sketch, plus brief+render), accepting plain-English requests, pasted documents, or concept images/sketches as vision input, and defaulting to direct JSON output with enable_thinking=False (though a reasoning trace can be enabled). While the stock base Qwen3.5-9B scores 0% on blueprint validity, Parti-Vision achieves ~67% schema-valid in-distribution and ~61% on unseen realistic prompts with free decoding — jumping to ~83% and ~97% respectively when served with vLLM's guided_json constrained decoding — though it remains an early research preview where roughly half of outputs contain at least one design slip (wrong pin nets, cost errors, misordered steps), making it a tool for rapid ideation and drafting rather than a substitute for real engineering, CAD, or safety review.

Model Files

File Name | Quant Type | File Size | File Link |

|-----------|------------|-----------|-----------|

| caid-technologies-parti-vision.BF16.gguf | BF16 | 17.9 GB | Download |

| caid-technologies-parti-vision.F16.gguf | F16 | 17.9 GB | Download |

| caid-technologies-parti-vision.Q3_K_L.gguf | Q3_K_L | 4.93 GB | Download |

| caid-technologies-parti-vision.Q3_K_M.gguf | Q3_K_M | 4.62 GB | Download |

| caid-technologies-parti-vision.Q3_K_S.gguf | Q3_K_S | 4.26 GB | Download |

| caid-technologies-parti-vision.Q4_K_M.gguf | Q4_K_M | 5.63 GB | Download |

| caid-technologies-parti-vision.Q4_K_S.gguf | Q4_K_S | 5.35 GB | Download |

| caid-technologies-parti-vision.Q5_K_M.gguf | Q5_K_M | 6.47 GB | Download |

| caid-technologies-parti-vision.Q5_K_S.gguf | Q5_K_S | 6.31 GB | Download |

| caid-technologies-parti-vision.Q8_0.gguf | Q8_0 | 9.53 GB | Download |

| caid-technologies-parti-vision.mmproj-bf16.gguf | mmproj-bf16 | 922 MB | Download |

| caid-technologies-parti-vision.mmproj-f16.gguf | mmproj-f16 | 922 MB | Download |

| caid-technologies-parti-vision.mmproj-q8_0.gguf | mmproj-q8_0 | 624 MB | Download |

llama.cpp

LLM inference in C/C++ — https://github.com/ggml-org/llama.cpp