Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,193 @@
+---
+license: mit
+language:
+  - en
+  - zh
+library_name: peft
+pipeline_tag: text-generation
+base_model: Qwen/Qwen3-30B-A3B-Instruct-2507
+base_model_relation: adapter
+tags:
+  - macaron
+  - a2ui
+  - a2ui-v0.8
+  - lora
+  - peft
+  - dynamic-ui
+  - structured-generation
+  - json-generation
+  - grpo
+  - qwen3
+---
+
+# Macaron A2UI Tall
+
+> This repository contains the LoRA adapter weights for **Macaron A2UI Tall**.
+
+Macaron A2UI Tall is a LoRA adapter trained to generate valid **A2UI v0.8** cards from user context. It is designed for dynamic UI generation in personal-agent scenarios, where a model converts conversation context, product state, and available actions into one structured UI card.
+
+This release corresponds to **Macaron A2UI Tall**.
+
+## Highlights
+
+- **A2UI v0.8 card generation**: generates structured UI cards that can be consumed by an A2UI-compatible renderer.
+- **LoRA adapter release**: lightweight adapter weights for continued training, inspection, and adaptation.
+- **Context-aware UI generation**: takes user intent, conversation context, product state, and available actions as input.
+- **GRPO post-training**: this release is produced with GRPO on top of a Qwen3-30B A2UI initialization.
+- **Validation-first design**: outputs should be checked by the provided A2UI v0.8 validator before rendering.
+
+## Model Overview
+
+| Field | Value |
+| --- | --- |
+| Model family | Macaron A2UI |
+| Variant | Tall |
+| Release name | `Macaron A2UI Tall` |
+| Release type | LoRA adapter |
+| Foundation checkpoint | `Qwen/Qwen3-30B-A3B-Instruct-2507` |
+| Target protocol | A2UI v0.8 |
+| Output format | JSON object with `text_response` and `a2ui` fields |
+| Training method | GRPO with LoRA |
+| Library | PEFT / Transformers |
+| Recommended dtype | bfloat16 |
+| Tokenizer | Same as foundation checkpoint |
+
+### Adapter Details
+
+| Field | Value |
+| --- | --- |
+| LoRA rank | `16` |
+| LoRA alpha | `32` |
+| LoRA dropout | `0.0` |
+| Target modules | `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj` |
+| LM head adapted | `No` |
+| Training max response | `4096` |
+
+## Model Variants
+
+| Variant | Release Name | Foundation Checkpoint | Release Type |
+| --- | --- | --- | --- |
+| Tall | Macaron A2UI Tall | `Qwen/Qwen3-30B-A3B-Instruct-2507` | LoRA adapter |
+| Grande | Macaron A2UI Grande | `Qwen/Qwen3-235B-A22B-Instruct-2507` | LoRA adapter |
+| Venti | Macaron A2UI Venti | `GLM 5.1` | LoRA adapter |
+
+You are currently viewing the **Tall** release.
+
+## Quickstart
+
+This repository contains adapter weights only. Load the corresponding foundation checkpoint first, then attach this adapter with PEFT.
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+import torch
+
+base_model_id = "Qwen/Qwen3-30B-A3B-Instruct-2507"
+adapter_id = "mindlab-research/Macaron-A2UI-Tall"
+
+tokenizer = AutoTokenizer.from_pretrained(
+    base_model_id,
+    trust_remote_code=True,
+)
+
+base_model = AutoModelForCausalLM.from_pretrained(
+    base_model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True,
+)
+
+model = PeftModel.from_pretrained(base_model, adapter_id)
+model.eval()
+
+messages = [
+    {
+        "role": "system",
+        "content": "You are an A2UI v0.8 card generation model. Output exactly one valid A2UI JSON card."
+    },
+    {
+        "role": "user",
+        "content": "<USER_CONTEXT_JSON>",
+    },
+]
+
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True,
+)
+
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=2048,
+    do_sample=False,
+)
+
+response = tokenizer.decode(
+    outputs[0][inputs.input_ids.shape[-1]:],
+    skip_special_tokens=True,
+)
+
+print(response)
+```
+
+## Output Contract
+
+Macaron A2UI Tall is trained to output:
+
+* valid JSON;
+* a top-level object of the form `{"text_response": "...", "a2ui": [...]}`;
+* no Markdown code fences;
+* no extra explanation outside the JSON object;
+* only A2UI actions and components supported by the calling product surface.
+
+The `a2ui` field is expected to contain A2UI v0.8 messages such as `beginRendering`, `surfaceUpdate`, `dataModelUpdate`, or `deleteSurface`.
+
+The model targets A2UI v0.8. Compatibility with later protocol revisions is not guaranteed without additional validation or fine-tuning.
+
+## Evaluation
+
+We evaluate Macaron A2UI on internal A2UI v0.8 card-generation benchmarks and product-aligned task suites.
+
+Public benchmark numbers and reproduction details are being standardized and will be added in a future revision of this model card.
+
+At the moment, this repository should be interpreted as an adapter release first. Evaluation methodology, task definitions, and comparable public results are still being consolidated.
+
+## Limitations
+
+Macaron A2UI Tall is specialized for A2UI generation and is not intended as a general-purpose chat model.
+
+Known limitations:
+
+* may generate valid JSON that is still semantically weak;
+* may hallucinate actions if the action space is underspecified;
+* may fail on A2UI versions other than v0.8;
+* requires external validation before production rendering;
+* should not be used for irreversible or safety-critical UI actions without user confirmation.
+
+## License
+
+The adapter weights are released under MIT.
+
+This adapter is trained on top of `Qwen/Qwen3-30B-A3B-Instruct-2507`. Users are responsible for complying with both:
+
+1. the adapter license;
+2. the license of the corresponding foundation checkpoint.
+
+## Citation
+
+```bibtex
+@misc{macaron_a2ui_tall,
+  title = {Macaron A2UI Tall},
+  author = {Mind Lab},
+  year = {2026},
+  publisher = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/mindlab-research/Macaron-A2UI-Tall}}
+}
+```
+
+## Contact
+
+contact@mindlab.ltd