Design-specialized vision-language model for UI/UX, visual creation, and multimodal design tasks. Instruction-tuned variant.
Fine-tuned from Qwen/Qwen3-VL-235B-A22B-Instruct (apache-2.0, Alibaba Qwen) with Hanzo identity + agentic-data training + abliteration. Not trained from scratch.
| Property | Value |
|---|---|
| Parameters | 235B total, 22B active (sparse MoE) |
| Architecture | Qwen3-VL MoE (Qwen3VLMoeForConditionalGeneration) |
| Modality | Vision-language (image understanding + text) |
| Context | 131K tokens |
from transformers import AutoModelForImageTextToText, AutoProcessor
model = AutoModelForImageTextToText.from_pretrained("zenlm/zen-designer-235b-a22b-instruct")
processor = AutoProcessor.from_pretrained("zenlm/zen-designer-235b-a22b-instruct")
messages = [{"role": "user", "content": [{"type": "text", "text": "Design a modern analytics dashboard."}]}]
inputs = processor.apply_chat_template(messages, add_generation_prompt=True, tokenize=True, return_tensors="pt")
out = model.generate(**inputs, max_new_tokens=512)
print(processor.decode(out[0], skip_special_tokens=True))
apache-2.0. Upstream: Qwen/Qwen3-VL-235B-A22B-Instruct by Alibaba Qwen (apache-2.0).
Built by Hanzo AI × Zoo Labs Foundation
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Submit a torrentHave the complete files and permission to share them? Replace the example folder path. The script checks the files, makes a torrent and submits its magnet and checksums. Keep your torrent client seeding. Get your community key from your settings, and read the script before running it.
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