Model card: no-wrap names and affiliations, narrower file tree

README.md

@@ -24,13 +24,14 @@ tags:
 # Scaling in Games: Continued Pre-Training for Embodied Agents in Diverse Virtual Worlds
 
 <p align="center" style="line-height:1.5;margin:0.4em 0 0.3em;">
-<b>Kuan Zhang</b><sup>1,2,*,‡</sup>, <b>Yukun Chen</b><sup>1,3,*,‡</sup>, <b>Zhihao Yang</b><sup>1,3,*,‡</sup>, Yue Su<sup>4</sup>, Xiangnan Wu<sup>3</sup>, Zirong Chen<sup>2</sup>, Run Luo<sup>1,5,‡</sup>, Jinkun Hou<sup>6</sup>, Tao Tan<sup>1</sup>, <b>Yinhe Zheng</b><sup>1,†</sup>, <b>Yiming Li</b><sup>2,†</sup>
+<span style="white-space:nowrap;"><b>Kuan Zhang</b><sup>1,2,*,‡</sup></span>, <span style="white-space:nowrap;"><b>Yukun Chen</b><sup>1,3,*,‡</sup></span>, <span style="white-space:nowrap;"><b>Zhihao Yang</b><sup>1,3,*,‡</sup></span>, <span style="white-space:nowrap;">Yue Su<sup>4</sup></span>, <span style="white-space:nowrap;">Xiangnan Wu<sup>3</sup></span>, <span style="white-space:nowrap;">Zirong Chen<sup>2</sup></span>, <span style="white-space:nowrap;">Run Luo<sup>1,5,‡</sup></span>, <span style="white-space:nowrap;">Jinkun Hou<sup>6</sup></span>, <span style="white-space:nowrap;">Tao Tan<sup>1</sup></span>, <span style="white-space:nowrap;"><b>Yinhe Zheng</b><sup>1,†</sup></span>, <span style="white-space:nowrap;"><b>Yiming Li</b><sup>2,†</sup></span>
 </p>
 
-<p align="center" style="font-size:0.85em;line-height:1.45;margin:0 0 0.6em;">
-<sup>1</sup>miHoYo Honkai AI R&amp;D Team &nbsp; <sup>2</sup>College AI, Tsinghua University &nbsp; <sup>3</sup>University of Chinese Academy of Sciences &nbsp; <sup>4</sup>MMLab, The University of Hong Kong &nbsp; <sup>5</sup>National University of Singapore &nbsp; <sup>6</sup>Peking University<br>
-<sup>*</sup>Equal contribution &nbsp; <sup>†</sup>Corresponding author &nbsp; <sup>‡</sup>Work done while interning at miHoYo
+<p align="center" style="font-size:0.85em;line-height:1.5;margin:0 0 0.6em;">
+<span style="white-space:nowrap;"><sup>1</sup>miHoYo Honkai AI R&amp;D Team</span> &nbsp; <span style="white-space:nowrap;"><sup>2</sup>College AI, Tsinghua University</span> &nbsp; <span style="white-space:nowrap;"><sup>3</sup>University of Chinese Academy of Sciences</span> &nbsp; <span style="white-space:nowrap;"><sup>4</sup>MMLab, The University of Hong Kong</span> &nbsp; <span style="white-space:nowrap;"><sup>5</sup>National University of Singapore</span> &nbsp; <span style="white-space:nowrap;"><sup>6</sup>Peking University</span><br>
+<span style="white-space:nowrap;"><sup>*</sup>Equal contribution</span> &nbsp; <span style="white-space:nowrap;"><sup>†</sup>Corresponding author</span> &nbsp; <span style="white-space:nowrap;"><sup>‡</sup>Work done while interning at miHoYo</span>
 </p>
+
 <p align="center">
   <img src="https://huggingface.co/THUSI-Lab/GameScaling/resolve/main/assets/logos/affiliations.png" alt="miHoYo · Tsinghua University · University of Chinese Academy of Sciences · The University of Hong Kong" width="100%" style="width:100%;max-width:100%;">
 </p>
@@ -84,15 +85,15 @@ training code. Paper results and analysis are on the [project page](https://game
 
 ```text
 THUSI-Lab/GameScaling
-├── models/
-│   ├── 0p8b_s1_1600h_gs6736/              one folder per checkpoint (eight in total)
-│   │   ├── config.json                    Qwen3_5ForConditionalGeneration, bfloat16
-│   │   ├── model.safetensors              weights (27B: model-0000{1,2}-of-00002 + index.json)
-│   │   ├── chat_template.jinja            REQUIRED: renders history turns exactly as in training
+├── models/                     eight checkpoints, one folder each
+│   ├── 0p8b_s1_1600h_gs6736/
+│   │   ├── config.json         Qwen3.5 architecture, bfloat16
+│   │   ├── model.safetensors   weights (27B: 2 shards + index)
+│   │   ├── chat_template.jinja required, renders history turns
 │   │   ├── tokenizer.json
 │   │   ├── tokenizer_config.json
 │   │   ├── generation_config.json
-│   │   ├── preprocessor_config.json       image processor
+│   │   ├── preprocessor_config.json
 │   │   ├── processor_config.json
 │   │   └── video_preprocessor_config.json
 │   ├── 0p8b_s3_1600h_gs6760/
@@ -103,22 +104,18 @@ THUSI-Lab/GameScaling
 │   ├── 27b_s1_1600h_gs6995/
 │   └── 27b_s3_1600h_gs7020/
 ├── prompts/
-│   ├── system_prompt_template.txt         standard system prompt with 3 placeholders (§2)
-│   └── example_doom_battle1.txt           a filled-in example
-├── gamescaling/                           inference client (requests + Pillow only)
-│   ├── __init__.py
-│   ├── prompt.py                          build_system_prompt / build_gameworld_system_prompt
-│   ├── policy.py                          GameScalingPolicy, PolicyConfig, presets, request body
-│   ├── action.py                          action format, parser, 74-token key vocabulary
-│   └── keymaps.py                         training key names <-> browser / Playwright keys
-├── scripts/
-│   └── serve_vllm.sh                      start an OpenAI-compatible vLLM server
-├── tests/
-│   └── test_core.py                       offline tests: prompts, requests, parsing (no GPU)
-├── assets/                                images used in this card
-├── requirements.txt                       client dependencies
-├── LICENSE                                Apache License 2.0
-└── README.md
+│   ├── system_prompt_template.txt  standard prompt, 3 slots (§2)
+│   └── example_doom_battle1.txt    filled-in example
+├── gamescaling/                inference client
+│   ├── prompt.py               system prompt builders
+│   ├── policy.py               client, presets, request body
+│   ├── action.py               action format and parser
+│   └── keymaps.py              key names <-> browser keys
+├── scripts/serve_vllm.sh       start a vLLM server
+├── tests/test_core.py          offline tests (no GPU)
+├── assets/                     images for this card
+├── requirements.txt            client deps: requests, Pillow
+└── LICENSE                     Apache 2.0
 ```
 
 ## 1. Download and serve