Add NanoAvatar models, bilingual model cards, and demo videos

.gitattributes

@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+android-qnn/quality/cpu_fp32/audio10_fp32.onnx.data filter=lfs diff=lfs merge=lfs -text
+android-qnn/quality/cpu_fp32/audio1_fp32.onnx.data filter=lfs diff=lfs merge=lfs -text
+android-qnn/quality/cpu_fp32/face_fp32.onnx.data filter=lfs diff=lfs merge=lfs -text
+assets/demo-en.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/demo-zh.mp4 filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,442 @@
+NanoAvatar Model License
+
+Chinese HuBERT and its floating-point, quantized, and Android-compiled versions retain the upstream MIT license. This applies to:
+full-precision/hubert_fp16.pt
+quantized/hubert_w8a16.pt
+Model files under android-qnn/models/hubert_flatgather_gelu_u16/
+
+Upstream model and publisher: https://huggingface.co/TencentGameMate/chinese-hubert-large
+Upstream project: https://github.com/TencentGameMate/chinese_speech_pretrain
+
+The following NanoAvatar lip-sync models and their quantized or compiled versions are licensed under CC BY-NC 4.0:
+full-precision/lip_fp32.pt
+quantized/lip_mixed_int8.pt
+Model files under android-qnn/quality/cpu_fp32/
+Model files under android-qnn/quality/generator/
+
+These models may be used for academic research and other noncommercial purposes, subject to attribution and the other terms of the license. Suggested attribution: NanoAvatar, with links to the project and license. Indicate modifications as required by the license.
+For commercial licensing, contact wupingyu@mail.ustc.edu.cn.
+Project: https://github.com/wpydcr/NanoAvatar
+License: https://creativecommons.org/licenses/by-nc/4.0/
+
+The licenses apply separately to the files listed above. They are not alternative license choices for the same file.
+
+===== MIT License Terms =====
+
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README.md

@@ -1,3 +1,74 @@
----
-license: cc-by-nc-4.0
----
+---
+language:
+- en
+- zh
+inference: false
+license: other
+license_name: nanoavatar-model-licenses
+license_link: LICENSE
+tags:
+  - nanoavatar
+  - talking-head
+  - lip-sync
+  - audio-driven
+  - audio-to-video
+  - real-time
+  - streaming
+---
+
+# NanoAvatar
+
+English | [简体中文](README.zh-CN.md) | [Code & Usage](https://github.com/wpydcr/NanoAvatar)
+
+**A lightweight model for real-time interactive avatars, deployable on edge devices.**
+
+On Snapdragon 8 Gen 3, the model achieves a measured throughput of **32 FPS**, with first-frame latency as low as **0.13 seconds**.
+
+Generate high-definition video in real time on edge devices to reduce avatar applications' reliance on cloud GPU servers. Even in cloud deployments, NanoAvatar can substantially reduce compute requirements.
+
+## Demos
+
+<table>
+  <tr>
+    <th align="center">English demo</th>
+    <th align="center">Chinese demo</th>
+  </tr>
+  <tr>
+    <td align="center" width="50%">
+      <video controls playsinline preload="metadata" width="280" style="max-width: 100%; height: auto;" src="https://huggingface.co/wpydcr/NanoAvatar/resolve/main/assets/demo-en.mp4" aria-label="English demo"></video>
+    </td>
+    <td align="center" width="50%">
+      <video controls playsinline preload="metadata" width="280" style="max-width: 100%; height: auto;" src="https://huggingface.co/wpydcr/NanoAvatar/resolve/main/assets/demo-zh.mp4" aria-label="Chinese demo"></video>
+    </td>
+  </tr>
+</table>
+
+## Models
+
+| Version | Directory | Contents |
+| --- | --- | --- |
+| Full precision | `full-precision/` | PyTorch: HuBERT FP16 and lip-sync model FP32 |
+| Quantized | `quantized/` | PyTorch/CUDA: HuBERT W8A16 and mixed INT8 lip-sync model |
+| Android compiled | `android-qnn/` | CPU: original FP32 face/audio encoders. QNN: HuBERT W8A16 and HTP FP16 generator |
+
+The Android build targets Snapdragon 8 Gen 3 / HTP v75.
+
+The model generates a **256 × 256 face region**, composited at the source video's resolution. Preserve the complete directory structure when downloading model files.
+
+## Performance
+
+| Version | Platform / device | Throughput (FPS) | First-frame latency (ms) | Memory / VRAM (MiB) |
+| --- | --- | ---: | ---: | ---: |
+| Android compiled | Z60 Ultra · Snapdragon 8 Gen 3<br>Android 14 | 32 | 127 | 785 |
+| Full precision | RTX 4090<br>Windows CUDA | 224 | 37 | 1119 |
+| Quantized | RTX 4090<br>Windows CUDA | 333 | 18 | 834 |
+
+## License
+
+[chinese-hubert-large](https://huggingface.co/TencentGameMate/chinese-hubert-large) and its quantized and compiled versions retain the upstream MIT license.
+
+Our lip-sync model and its quantized and compiled versions use [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). Academic research and other noncommercial uses are permitted, subject to attribution and the other license terms.
+
+**Commercial licensing:** [wupingyu@mail.ustc.edu.cn](mailto:wupingyu@mail.ustc.edu.cn).
+
+See [LICENSE](LICENSE) for the full terms.

README.zh-CN.md

@@ -0,0 +1,58 @@
+# NanoAvatar
+
+[English](README.md) | 简体中文 | [源码与使用](https://github.com/wpydcr/NanoAvatar)
+
+**可端侧部署的实时交互数字人的轻量模型。**
+
+在骁龙 8 Gen 3上模型吞吐实测 **32 FPS**，首帧延迟低至 **0.13 秒**。
+
+通过端侧实时生成高清视频，减少数字人应用对云端 GPU 服务器的依赖。
+即使是云端应用，也能大幅减少算力消耗。
+
+## 视频演示
+
+<table>
+  <tr>
+    <th align="center">中文演示</th>
+    <th align="center">英文演示</th>
+  </tr>
+  <tr>
+    <td align="center" width="50%">
+      <video controls playsinline preload="metadata" width="280" style="max-width: 100%; height: auto;" src="https://huggingface.co/wpydcr/NanoAvatar/resolve/main/assets/demo-zh.mp4" aria-label="中文演示"></video>
+    </td>
+    <td align="center" width="50%">
+      <video controls playsinline preload="metadata" width="280" style="max-width: 100%; height: auto;" src="https://huggingface.co/wpydcr/NanoAvatar/resolve/main/assets/demo-en.mp4" aria-label="英文演示"></video>
+    </td>
+  </tr>
+</table>
+
+## 模型
+
+| 版本 | 目录 | 内容 |
+| --- | --- | --- |
+| 全精度 | `full-precision/` | PyTorch：HuBERT FP16、口播模型 FP32 |
+| 量化版 | `quantized/` | PyTorch/CUDA：HuBERT W8A16、口播模型混合 INT8 |
+| Android 编译版 | `android-qnn/` | CPU：人脸/音频编码器原始 FP32；QNN：HuBERT W8A16、生成器 HTP FP16 |
+
+Android 编译版面向骁龙 8 Gen 3 / HTP v75。
+
+模型生成人脸区域的分辨率为 **256 × 256**，最终画面按原视频尺寸合成。下载模型时请保留完整目录结构。
+
+## 性能参考
+
+| 版本 | 平台 / 设备 | 生成吞吐（FPS） | 首帧延迟（ms） | 内存 / 显存（MiB） |
+| --- | --- | ---: | ---: | ---: |
+| Android 编译版 | Z60 Ultra · 骁龙 8 Gen 3<br>Android 14 | 32 | 127 | 785 |
+| 全精度 | RTX 4090<br>Windows CUDA | 224 | 37 | 1119 |
+| 量化版 | RTX 4090<br>Windows CUDA | 333 | 18 | 834 |
+
+
+## 许可
+
+[chinese-hubert-large](https://huggingface.co/TencentGameMate/chinese-hubert-large) 及其量化、编译版本继承上游 MIT 许可。
+
+我们自己的口播模型及其量化、编译版本采用 [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/)，可在遵守署名等许可条件的前提下用于学术研究及其他非商业用途。
+
+**商业授权：**[wupingyu@mail.ustc.edu.cn](mailto:wupingyu@mail.ustc.edu.cn)。
+
+完整许可条款见 [LICENSE](LICENSE)。

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