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.agents/skills/tilelang-ascend-kernel/SKILL.md

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## References
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Read `docs/en/dev_guide/tilelang_ascend_kernel_dev.md` for mechanism details.
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Read [tilelang_ascend_kernel_dev](https://docs.xllm-ai.com/en/dev_guide/tilelang_ascend_kernel_dev/) for mechanism details.
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Use `rope` as the concrete template:
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- `xllm/compiler/tilelang/targets/ascend/kernels/rope.py`
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- `xllm/core/kernels/npu/tilelang/rope_wrapper.cpp`

MANIFEST.in

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recursive-include xllm *.py
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recursive-include examples *.py
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recursive-include third_party *
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recursive-include docs *.*
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recursive-include tools *.*
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recursive-include scripts *.*
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recursive-include proto *.*

README.md

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See the License for the specific language governing permissions and
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limitations under the License. -->
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[English](./README.md) | [中文](./docs/project/README_zh.md)
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[English](./README.md) | [中文](./README_zh.md)
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<div align="center">
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<img src="docs/assets/logo_with_llm.png" alt="xLLM" style="width:50%; height:auto;">
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<img src="assets/logo_with_llm.png" alt="xLLM" style="width:50%; height:auto;">
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2020
[![Document](https://img.shields.io/badge/Document-black?logo=html5&labelColor=grey&color=red)](https://docs.xllm-ai.com/) [![Docker](https://img.shields.io/badge/Docker-black?logo=docker&labelColor=grey&color=%231E90FF)](https://quay.io/repository/jd_xllm/xllm-ai?tab=tags) [![License](https://img.shields.io/badge/license-Apache%202.0-brightgreen?labelColor=grey)](https://opensource.org/licenses/Apache-2.0) [![report](https://img.shields.io/badge/Technical%20Report-red?logo=arxiv&logoColor=%23B31B1B&labelColor=%23F0EBEB&color=%23D42626)](https://arxiv.org/abs/2510.14686) [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/jd-opensource/xllm)
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**xLLM** is an **efficient LLM inference framework**, specifically optimized for **Chinese AI accelerators**, enabling enterprise-grade deployment with enhanced efficiency and reduced cost.
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<div align="center">
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<img src="docs/assets/xllm_arch.png" alt="xllm_arch" style="width:90%; height:auto;">
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<img src="assets/xllm_arch.png" alt="xllm_arch" style="width:90%; height:auto;">
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</div>
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## Highlights
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## Community & Support
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<div align="center">
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<img src="docs/assets/wechat_qrcode.png" alt="qrcode3" width="50%" />
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<img src="assets/wechat_qrcode.png" alt="qrcode3" width="50%" />
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</div>
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## Acknowledgment
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See the License for the specific language governing permissions and
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limitations under the License. -->
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[English](../../README.md) | [中文](./README_zh.md)
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[English](./README.md) | [中文](./README_zh.md)
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<div align="center">
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<img src="../assets/logo_with_llm.png" alt="xLLM" style="width:50%; height:auto;">
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<img src="assets/logo_with_llm.png" alt="xLLM" style="width:50%; height:auto;">
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2020
[![Document](https://img.shields.io/badge/Document-black?logo=html5&labelColor=grey&color=red)](https://docs.xllm-ai.com/) [![Docker](https://img.shields.io/badge/Docker-black?logo=docker&labelColor=grey&color=%231E90FF)](https://quay.io/repository/jd_xllm/xllm-ai?tab=tags) [![License](https://img.shields.io/badge/license-Apache%202.0-brightgreen?labelColor=grey)](https://opensource.org/licenses/Apache-2.0) [![report](https://img.shields.io/badge/Technical%20Report-red?logo=arxiv&logoColor=%23B31B1B&labelColor=%23F0EBEB&color=%23D42626)](https://arxiv.org/abs/2510.14686) [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/jd-opensource/xllm)
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**xLLM** 是一个高效的开源大模型推理框架,专为**国产芯片**优化设计,提供企业级的服务部署,使得性能更高、成本更低。
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<div align="center">
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<img src="../assets/xllm_arch.png" alt="xllm_arch" style="width:90%; height:auto;">
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<img src="assets/xllm_arch.png" alt="xllm_arch" style="width:90%; height:auto;">
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</div>
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## 亮点
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## 社区支持
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<img src="../assets/wechat_qrcode.png" alt="qrcode3" width="50%" />
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<img src="assets/wechat_qrcode.png" alt="qrcode3" width="50%" />
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</div>
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journal={arXiv preprint arXiv:2510.14686},
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year={2025}
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}
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```
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```
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### Docs
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- Add getting started docs.
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- Add features docs.
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- Add features docs.
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