Text Generation
PEFT
Safetensors
English
Chinese
macaron
a2ui
a2ui-v0.8
lora
dynamic-ui
structured-generation
json-generation
grpo
qwen3
Instructions to use mindlab-research/Macaron-A2UI-Tall with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mindlab-research/Macaron-A2UI-Tall with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/vePFS-Mindverse/share/huggingface/hub/models--Qwen--Qwen3-30B-A3B-Instruct-2507/snapshots/0d7cf23991f47feeb3a57ecb4c9cee8ea4a17bfe") model = PeftModel.from_pretrained(base_model, "mindlab-research/Macaron-A2UI-Tall") - Notebooks
- Google Colab
- Kaggle
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# Macaron-A2UI: A Model for Generative UI in Personal Agents
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> This repository contains the LoRA adapter weights for **Macaron A2UI Tall**.
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# Macaron-A2UI: A Model for Generative UI in Personal Agents
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<b>📰 <a href="https://huggingface.co/mindlab-research/Macaron-A2UI-Tall/blob/main/Macaron_A2UI.pdf">Technical Report</a></b> | <b>📄 <a href="https://arxiv.org/abs/2605.24830">Paper</a></b>
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> This repository contains the LoRA adapter weights for **Macaron A2UI Tall**.
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