From f2b2fb5d6b8f58287c84d7da4d7603f402b72c63 Mon Sep 17 00:00:00 2001 From: "zhangxu.709" Date: Mon, 6 Jul 2026 17:17:42 +0800 Subject: [PATCH] chore: update github utl to xllm-ai. --- README.md | 4 ++-- README.zh-CN.md | 4 ++-- .../en/cookbook/autoregressive_models/glm/glm_5.md | 10 +++++----- .../en/cookbook/autoregressive_models/kimi/kimi2_5.md | 4 ++-- .../autoregressive_models/minmax/minmax_m2_7.md | 4 ++-- .../en/cookbook/autoregressive_models/qwen/qwen3_5.md | 4 ++-- .../docs/en/cookbook/diffusion_models/flux/flux2.md | 4 ++-- src/content/docs/en/features/disagg_pd.md | 2 +- src/content/docs/en/features/global_kvcache.md | 2 +- src/content/docs/en/features/xllm_service_overview.md | 2 +- src/content/docs/en/getting_started/offline_service.md | 8 ++++---- src/content/docs/en/getting_started/quick_start.md | 4 ++-- .../zh/cookbook/autoregressive_models/glm/glm_5.md | 10 +++++----- .../zh/cookbook/autoregressive_models/kimi/kimi2_5.md | 4 ++-- .../autoregressive_models/minmax/minmax_m2_7.md | 4 ++-- .../zh/cookbook/autoregressive_models/qwen/qwen3_5.md | 4 ++-- .../docs/zh/cookbook/diffusion_models/flux/flux2.md | 4 ++-- src/content/docs/zh/features/disagg_pd.md | 2 +- src/content/docs/zh/features/global_kvcache.md | 2 +- src/content/docs/zh/features/xllm_service_overview.md | 2 +- src/content/docs/zh/getting_started/offline_service.md | 8 ++++---- src/content/docs/zh/getting_started/quick_start.md | 4 ++-- 22 files changed, 48 insertions(+), 48 deletions(-) diff --git a/README.md b/README.md index b55d995..bea6ed4 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,7 @@ [English](./README.md) | [简体中文](./README.zh-CN.md) This repository contains the Astro + Starlight documentation site for -[xLLM](https://github.com/jd-opensource/xllm), an LLM inference framework for +[xLLM](https://github.com/xLLM-AI/xllm), an LLM inference framework for high-performance serving on domestic AI accelerators. The site is built with Starlight and `starlight-theme-rapide`. It includes a @@ -85,4 +85,4 @@ npm run preview ## Related Repository -- xLLM source code: +- xLLM source code: diff --git a/README.zh-CN.md b/README.zh-CN.md index ca67f73..0ccbc1b 100644 --- a/README.zh-CN.md +++ b/README.zh-CN.md @@ -2,7 +2,7 @@ [English](./README.md) | [简体中文](./README.zh-CN.md) -本仓库是 [xLLM](https://github.com/jd-opensource/xllm) 的 Astro + Starlight +本仓库是 [xLLM](https://github.com/xLLM-AI/xllm) 的 Astro + Starlight 文档站。xLLM 是面向国产 AI 加速器的高性能大语言模型推理框架。 站点基于 Starlight 和 `starlight-theme-rapide` 构建，包含自定义顶部导航、 @@ -81,4 +81,4 @@ npm run preview ## 相关仓库 -- xLLM 源码： +- xLLM 源码： diff --git a/src/content/docs/en/cookbook/autoregressive_models/glm/glm_5.md b/src/content/docs/en/cookbook/autoregressive_models/glm/glm_5.md index 68404cb..fac8101 100644 --- a/src/content/docs/en/cookbook/autoregressive_models/glm/glm_5.md +++ b/src/content/docs/en/cookbook/autoregressive_models/glm/glm_5.md @@ -3,7 +3,7 @@ title: "GLM-5 / GLM-5.1 / GLM-5.2" sidebar: order: 2 --- -+ Source code: https://github.com/jd-opensource/xllm ++ Source code: https://github.com/xLLM-AI/xllm + Available in China: https://gitcode.com/xLLM-AI/xllm @@ -57,7 +57,7 @@ sudo docker run -it --ipc=host -u 0 --privileged --name mydocker --network=host Download the official repository and module dependencies: ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm git checkout release/v0.10.0 git submodule update --init --recursive @@ -339,15 +339,15 @@ msmodelslim quant \ #### PD Disaggregated Deployment -`xllm` supports PD disaggregated deployment. This must be used together with another open-source library, [xllm service](https://github.com/jd-opensource/xllm-service). +`xllm` supports PD disaggregated deployment. This must be used together with another open-source library, [xllm service](https://github.com/xLLM-AI/xllm-service). ##### xLLM Service Dependencies First, download and install `xllm service`, similar to installing and building `xllm`: ```bash -git clone https://github.com/jd-opensource/xllm-service -cd xllm_service +git clone https://github.com/xLLM-AI/xllm-service.git +cd xllm-service git submodule init git submodule update ``` diff --git a/src/content/docs/en/cookbook/autoregressive_models/kimi/kimi2_5.md b/src/content/docs/en/cookbook/autoregressive_models/kimi/kimi2_5.md index b7e720f..00c2156 100644 --- a/src/content/docs/en/cookbook/autoregressive_models/kimi/kimi2_5.md +++ b/src/content/docs/en/cookbook/autoregressive_models/kimi/kimi2_5.md @@ -4,7 +4,7 @@ sidebar: order: 2 --- -- Source code: [https://github.com/jd-opensource/xllm](https://github.com/jd-opensource/xllm) +- Source code: [https://github.com/xLLM-AI/xllm](https://github.com/xLLM-AI/xllm) - Available in China: [https://gitcode.com/xLLM-AI/xllm](https://gitcode.com/xLLM-AI/xllm) - Kimi-K2.5 W8A8 weight download: [modelscope-Kimi-K2.5-W8A8-xLLM](https://www.modelscope.cn/models/Eco-Tech/Kimi-K2.5-W8A8-xLLM) - Kimi-K2.6 W8A8 weight download: [modelscope-Kimi-K2.6-w8a8-xllm](https://www.modelscope.cn/models/Eco-Tech/Kimi-K2.6-w8a8-xllm) @@ -55,7 +55,7 @@ sudo docker run -it --ipc=host -u 0 --privileged --name xllm_kimi_k25 --network= Download the official repository and module dependencies: ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm git checkout main git submodule init diff --git a/src/content/docs/en/cookbook/autoregressive_models/minmax/minmax_m2_7.md b/src/content/docs/en/cookbook/autoregressive_models/minmax/minmax_m2_7.md index b8748f6..89bb876 100644 --- a/src/content/docs/en/cookbook/autoregressive_models/minmax/minmax_m2_7.md +++ b/src/content/docs/en/cookbook/autoregressive_models/minmax/minmax_m2_7.md @@ -4,7 +4,7 @@ sidebar: order: 3 --- -+ Source code: https://github.com/jd-opensource/xllm ++ Source code: https://github.com/xLLM-AI/xllm + Available in China: https://gitcode.com/xLLM-AI/xllm @@ -73,7 +73,7 @@ sudo docker run -it --ipc=host -u 0 --privileged --name xllm_minimax --network=h Download the official repository and module dependencies: ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm git checkout preview/minimax-minimal git submodule init diff --git a/src/content/docs/en/cookbook/autoregressive_models/qwen/qwen3_5.md b/src/content/docs/en/cookbook/autoregressive_models/qwen/qwen3_5.md index da72f69..23bfba0 100644 --- a/src/content/docs/en/cookbook/autoregressive_models/qwen/qwen3_5.md +++ b/src/content/docs/en/cookbook/autoregressive_models/qwen/qwen3_5.md @@ -4,7 +4,7 @@ sidebar: order: 1 --- -+ Source code: https://github.com/jd-opensource/xllm ++ Source code: https://github.com/xLLM-AI/xllm + Available in China: https://gitcode.com/xLLM-AI/xllm @@ -57,7 +57,7 @@ docker run -it -d \ Download the official repository and module dependencies: ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm pip install pre-commit pre-commit install diff --git a/src/content/docs/en/cookbook/diffusion_models/flux/flux2.md b/src/content/docs/en/cookbook/diffusion_models/flux/flux2.md index 9d243c2..2d98560 100644 --- a/src/content/docs/en/cookbook/diffusion_models/flux/flux2.md +++ b/src/content/docs/en/cookbook/diffusion_models/flux/flux2.md @@ -7,7 +7,7 @@ sidebar: This section will collect Flux2 diffusion model inference recipes for xLLM. -+ Source code: https://github.com/jd-opensource/xllm ++ Source code: https://github.com/xLLM-AI/xllm + Available in China: https://gitcode.com/xLLM-AI/xllm @@ -57,7 +57,7 @@ docker exec -it $CONTAINER bash Download the official repository and module dependencies: ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm ``` diff --git a/src/content/docs/en/features/disagg_pd.md b/src/content/docs/en/features/disagg_pd.md index 6b013e8..2a0edad 100644 --- a/src/content/docs/en/features/disagg_pd.md +++ b/src/content/docs/en/features/disagg_pd.md @@ -20,7 +20,7 @@ The overall architecture is shown below: ### Preparation #### Install Dependencies - **xLLM**: Refer to [Installation && Compilation](/en/getting_started/quick_start/) -- **xLLM Service**: Refer to [xLLM Service](https://github.com/jd-opensource/xllm-service) +- **xLLM Service**: Refer to [xLLM Service](https://github.com/xLLM-AI/xllm-service) #### Obtain Environment Information Deploying Disaggregated PD Service requires obtaining the Device IP of the machine to create communication resources. Execute the command `cat /etc/hccn.conf | grep address` on the current AI Server to get the Device IP, for example: diff --git a/src/content/docs/en/features/global_kvcache.md b/src/content/docs/en/features/global_kvcache.md index 9c1f282..a12e16d 100644 --- a/src/content/docs/en/features/global_kvcache.md +++ b/src/content/docs/en/features/global_kvcache.md @@ -21,7 +21,7 @@ The overall architecture is shown in the diagram below: #### Install Dependencies - **xLLM**: Refer to [Quick Start](/en/getting_started/quick_start/) -- **xLLM Service**: Refer to [xLLM Service](https://github.com/jd-opensource/xllm-service) +- **xLLM Service**: Refer to [xLLM Service](https://github.com/xLLM-AI/xllm-service) ### Usage Instructions diff --git a/src/content/docs/en/features/xllm_service_overview.md b/src/content/docs/en/features/xllm_service_overview.md index b6e10fe..0f7ecce 100644 --- a/src/content/docs/en/features/xllm_service_overview.md +++ b/src/content/docs/en/features/xllm_service_overview.md @@ -3,7 +3,7 @@ title: "xLLM Service" sidebar: order: 90 --- -[:simple-github: xLLM Service](https://github.com/jd-opensource/xllm-service) +[:simple-github: xLLM Service](https://github.com/xLLM-AI/xllm-service) ## Project Overview diff --git a/src/content/docs/en/getting_started/offline_service.md b/src/content/docs/en/getting_started/offline_service.md index 437bf3f..5bc87cf 100644 --- a/src/content/docs/en/getting_started/offline_service.md +++ b/src/content/docs/en/getting_started/offline_service.md @@ -7,9 +7,9 @@ To facilitate users in quickly using xLLM for offline inference, we provide Pyth ## LLM -LLM inference example: [:simple-github: https://github.com/jd-opensource/xllm/blob/main/examples/generate.py](https://github.com/jd-opensource/xllm/blob/main/examples/generate.py) +LLM inference example: [:simple-github: https://github.com/xLLM-AI/xllm/blob/main/examples/generate.py](https://github.com/xLLM-AI/xllm/blob/main/examples/generate.py) -LLM Beam Search example: [:simple-github: https://github.com/jd-opensource/xllm/blob/main/examples/generate_beam_search.py](https://github.com/jd-opensource/xllm/blob/main/examples/generate_beam_search.py) +LLM Beam Search example: [:simple-github: https://github.com/xLLM-AI/xllm/blob/main/examples/generate_beam_search.py](https://github.com/xLLM-AI/xllm/blob/main/examples/generate_beam_search.py) Use `BeamSearchParams` with `beam_width` greater than `1`, then call `llm.beam_search(...)`: @@ -36,8 +36,8 @@ For LLM Beam Search, use `beam_width` as the switch. `top_logprobs` controls the ## Embedding -Generate embedding example: [:simple-github: https://github.com/jd-opensource/xllm/blob/main/examples/generate_embedding.py](https://github.com/jd-opensource/xllm/blob/main/examples/generate_embedding.py) +Generate embedding example: [:simple-github: https://github.com/xLLM-AI/xllm/blob/main/examples/generate_embedding.py](https://github.com/xLLM-AI/xllm/blob/main/examples/generate_embedding.py) ## VLM -VLM inference example: [:simple-github: https://github.com/jd-opensource/xllm/blob/main/examples/generate_vlm.py](https://github.com/jd-opensource/xllm/blob/main/examples/generate_vlm.py) +VLM inference example: [:simple-github: https://github.com/xLLM-AI/xllm/blob/main/examples/generate_vlm.py](https://github.com/xLLM-AI/xllm/blob/main/examples/generate_vlm.py) diff --git a/src/content/docs/en/getting_started/quick_start.md b/src/content/docs/en/getting_started/quick_start.md index 5aa2bd1..3281d63 100644 --- a/src/content/docs/en/getting_started/quick_start.md +++ b/src/content/docs/en/getting_started/quick_start.md @@ -47,7 +47,7 @@ docker run -it \ ### NVIDIA GPU -We provide a [Dockerfile](https://github.com/jd-opensource/xllm/blob/main/docker/Dockerfile.cuda) for NVIDIA GPU usage, which can be used to build custom image. Of course, you can also use dev image we built based on the default Dockerfile: +We provide a [Dockerfile](https://github.com/xLLM-AI/xllm/blob/main/docker/Dockerfile.cuda) for NVIDIA GPU usage, which can be used to build custom image. Of course, you can also use dev image we built based on the default Dockerfile: ```bash docker pull quay.io/jd_xllm/xllm-ai:xllm-dev-cuda-x86 ``` @@ -148,7 +148,7 @@ If you download a release image, i.e., an image with a version number in the tag Download xllm and dependencies: ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm # Install pre-commit for the first time diff --git a/src/content/docs/zh/cookbook/autoregressive_models/glm/glm_5.md b/src/content/docs/zh/cookbook/autoregressive_models/glm/glm_5.md index e3f8276..1037900 100644 --- a/src/content/docs/zh/cookbook/autoregressive_models/glm/glm_5.md +++ b/src/content/docs/zh/cookbook/autoregressive_models/glm/glm_5.md @@ -4,7 +4,7 @@ sidebar: order: 2 --- -+ 源码地址：https://github.com/jd-opensource/xllm ++ 源码地址：https://github.com/xLLM-AI/xllm + 国内可用: https://gitcode.com/xLLM-AI/xllm @@ -58,7 +58,7 @@ sudo docker run -it --ipc=host -u 0 --privileged --name mydocker --network=host 下载官方仓库与模块依赖： ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm git checkout release/v0.10.0 git submodule update --init --recursive @@ -330,15 +330,15 @@ msmodelslim quant \ #### PD分离部署 -`xllm`支持PD分离部署，这需要与另一个开源库[xllm service](https://github.com/jd-opensource/xllm-service)配套使用。 +`xllm`支持PD分离部署，这需要与另一个开源库[xllm service](https://github.com/xLLM-AI/xllm-service)配套使用。 ##### xLLM Service依赖 首先，我们下载安装`xllm service`，与安装编译`xllm`类似： ```bash -git clone https://github.com/jd-opensource/xllm-service -cd xllm_service +git clone https://github.com/xLLM-AI/xllm-service.git +cd xllm-service git submodule init git submodule update ``` diff --git a/src/content/docs/zh/cookbook/autoregressive_models/kimi/kimi2_5.md b/src/content/docs/zh/cookbook/autoregressive_models/kimi/kimi2_5.md index 759db44..67c50d7 100644 --- a/src/content/docs/zh/cookbook/autoregressive_models/kimi/kimi2_5.md +++ b/src/content/docs/zh/cookbook/autoregressive_models/kimi/kimi2_5.md @@ -4,7 +4,7 @@ sidebar: order: 2 --- -- 源码地址：[https://github.com/jd-opensource/xllm](https://github.com/jd-opensource/xllm) +- 源码地址：[https://github.com/xLLM-AI/xllm](https://github.com/xLLM-AI/xllm) - 国内可用: [https://gitcode.com/xLLM-AI/xllm](https://gitcode.com/xLLM-AI/xllm) - Kimi-K2.5 W8A8权重下载: [modelscope-Kimi-K2.5-W8A8-xLLM](https://www.modelscope.cn/models/Eco-Tech/Kimi-K2.5-W8A8-xLLM) - Kimi-K2.6 W8A8权重下载: [modelscope-Kimi-K2.6-w8a8-xllm](https://www.modelscope.cn/models/Eco-Tech/Kimi-K2.6-w8a8-xllm) @@ -55,7 +55,7 @@ sudo docker run -it --ipc=host -u 0 --privileged --name xllm_kimi_k25 --network= 下载官方仓库与模块依赖： ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm git checkout main git submodule init diff --git a/src/content/docs/zh/cookbook/autoregressive_models/minmax/minmax_m2_7.md b/src/content/docs/zh/cookbook/autoregressive_models/minmax/minmax_m2_7.md index 1738a46..2fc02f1 100644 --- a/src/content/docs/zh/cookbook/autoregressive_models/minmax/minmax_m2_7.md +++ b/src/content/docs/zh/cookbook/autoregressive_models/minmax/minmax_m2_7.md @@ -4,7 +4,7 @@ sidebar: order: 3 --- -+ 源码地址：https://github.com/jd-opensource/xllm ++ 源码地址：https://github.com/xLLM-AI/xllm + 国内可用: https://gitcode.com/xLLM-AI/xllm @@ -73,7 +73,7 @@ sudo docker run -it --ipc=host -u 0 --privileged --name xllm_minimax --network=h 下载官方仓库与模块依赖： ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm git checkout preview/minimax-minimal git submodule init diff --git a/src/content/docs/zh/cookbook/autoregressive_models/qwen/qwen3_5.md b/src/content/docs/zh/cookbook/autoregressive_models/qwen/qwen3_5.md index 1cb9f4d..d1d83a6 100644 --- a/src/content/docs/zh/cookbook/autoregressive_models/qwen/qwen3_5.md +++ b/src/content/docs/zh/cookbook/autoregressive_models/qwen/qwen3_5.md @@ -4,7 +4,7 @@ sidebar: order: 1 --- -+ 源码地址：https://github.com/jd-opensource/xllm ++ 源码地址：https://github.com/xLLM-AI/xllm + 国内可用: https://gitcode.com/xLLM-AI/xllm @@ -57,7 +57,7 @@ docker run -it -d \ 下载官方仓库与模块依赖： ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm pip install pre-commit pre-commit install diff --git a/src/content/docs/zh/cookbook/diffusion_models/flux/flux2.md b/src/content/docs/zh/cookbook/diffusion_models/flux/flux2.md index 5c171c9..950945f 100644 --- a/src/content/docs/zh/cookbook/diffusion_models/flux/flux2.md +++ b/src/content/docs/zh/cookbook/diffusion_models/flux/flux2.md @@ -7,7 +7,7 @@ sidebar: 本章节用于汇总 Flux2 扩散模型在 xLLM 中的推理实践。 -+ 源码地址：https://github.com/jd-opensource/xllm ++ 源码地址：https://github.com/xLLM-AI/xllm + 国内可用: https://gitcode.com/xLLM-AI/xllm @@ -58,7 +58,7 @@ docker exec -it $CONTAINER bash 下载官方仓库与模块依赖： ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm ``` diff --git a/src/content/docs/zh/features/disagg_pd.md b/src/content/docs/zh/features/disagg_pd.md index d940a4b..4dbdd6b 100644 --- a/src/content/docs/zh/features/disagg_pd.md +++ b/src/content/docs/zh/features/disagg_pd.md @@ -18,7 +18,7 @@ xLLM PD分离功能主要通过以下三个模块实现： ### 使用准备 #### 安装相关依赖 - **xLLM**: 参见[安装编译](/zh/getting_started/quick_start/) -- **xLLM Service**: 参见[xLLM Service](https://github.com/jd-opensource/xllm-service) +- **xLLM Service**: 参见[xLLM Service](https://github.com/xLLM-AI/xllm-service) ### 启动PD分离服务 1. 启动etcd diff --git a/src/content/docs/zh/features/global_kvcache.md b/src/content/docs/zh/features/global_kvcache.md index b7570d6..fb4ffd8 100644 --- a/src/content/docs/zh/features/global_kvcache.md +++ b/src/content/docs/zh/features/global_kvcache.md @@ -18,7 +18,7 @@ xLLM 全局KV Cache功能主要通过以下三个模块实现： ### 使用准备 #### 安装相关依赖 - **xLLM**: 参见[快速开始](/zh/getting_started/quick_start/) -- **xLLM Service**: 参见[xLLM Service](https://github.com/jd-opensource/xllm-service) +- **xLLM Service**: 参见[xLLM Service](https://github.com/xLLM-AI/xllm-service) ### 使用方式 1. etcd启动配置： diff --git a/src/content/docs/zh/features/xllm_service_overview.md b/src/content/docs/zh/features/xllm_service_overview.md index e538276..f25b27c 100644 --- a/src/content/docs/zh/features/xllm_service_overview.md +++ b/src/content/docs/zh/features/xllm_service_overview.md @@ -3,7 +3,7 @@ title: "xLLM Service" sidebar: order: 90 --- -[:simple-github: xLLM Service](https://github.com/jd-opensource/xllm-service) +[:simple-github: xLLM Service](https://github.com/xLLM-AI/xllm-service) ## 简介 diff --git a/src/content/docs/zh/getting_started/offline_service.md b/src/content/docs/zh/getting_started/offline_service.md index 08f1105..c9b9fbd 100644 --- a/src/content/docs/zh/getting_started/offline_service.md +++ b/src/content/docs/zh/getting_started/offline_service.md @@ -7,9 +7,9 @@ sidebar: ## LLM -LLM推理示例：[:simple-github: https://github.com/jd-opensource/xllm/blob/main/examples/generate.py](https://github.com/jd-opensource/xllm/blob/main/examples/generate.py) +LLM推理示例：[:simple-github: https://github.com/xLLM-AI/xllm/blob/main/examples/generate.py](https://github.com/xLLM-AI/xllm/blob/main/examples/generate.py) -LLM Beam Search 示例：[:simple-github: https://github.com/jd-opensource/xllm/blob/main/examples/generate_beam_search.py](https://github.com/jd-opensource/xllm/blob/main/examples/generate_beam_search.py) +LLM Beam Search 示例：[:simple-github: https://github.com/xLLM-AI/xllm/blob/main/examples/generate_beam_search.py](https://github.com/xLLM-AI/xllm/blob/main/examples/generate_beam_search.py) 使用 `BeamSearchParams` 设置大于 `1` 的 `beam_width`，然后调用 `llm.beam_search(...)`： @@ -36,9 +36,9 @@ LLM Beam Search 使用 `beam_width` 作为开启参数。`top_logprobs` 控制 ## Embedding -生成Embedding示例：[:simple-github: https://github.com/jd-opensource/xllm/blob/main/examples/generate_embedding.py](https://github.com/jd-opensource/xllm/blob/main/examples/generate_embedding.py) +生成Embedding示例：[:simple-github: https://github.com/xLLM-AI/xllm/blob/main/examples/generate_embedding.py](https://github.com/xLLM-AI/xllm/blob/main/examples/generate_embedding.py) ## VLM -VLM推理示例：[:simple-github: https://github.com/jd-opensource/xllm/blob/main/examples/generate_vlm.py](https://github.com/jd-opensource/xllm/blob/main/examples/generate_vlm.py) +VLM推理示例：[:simple-github: https://github.com/xLLM-AI/xllm/blob/main/examples/generate_vlm.py](https://github.com/xLLM-AI/xllm/blob/main/examples/generate_vlm.py) diff --git a/src/content/docs/zh/getting_started/quick_start.md b/src/content/docs/zh/getting_started/quick_start.md index a95a8c2..e463e9d 100644 --- a/src/content/docs/zh/getting_started/quick_start.md +++ b/src/content/docs/zh/getting_started/quick_start.md @@ -47,7 +47,7 @@ docker run -it \ ### NVIDIA GPU -我们提供了NVIDIA GPU使用的[Dockerfile](https://github.com/jd-opensource/xllm/blob/main/docker/Dockerfile.cuda)，可以构建自定义镜像，当然也可以使用我们根据默认Dockerfile构建的开发镜像： +我们提供了NVIDIA GPU使用的[Dockerfile](https://github.com/xLLM-AI/xllm/blob/main/docker/Dockerfile.cuda)，可以构建自定义镜像，当然也可以使用我们根据默认Dockerfile构建的开发镜像： ```bash docker pull quay.io/jd_xllm/xllm-ai:xllm-dev-cuda-x86 ``` @@ -148,7 +148,7 @@ docker run -it \ 下载xllm及依赖 ```bash -git clone https://github.com/jd-opensource/xllm +git clone https://github.com/xLLM-AI/xllm.git cd xllm # 第一次需要进行pre-commit安装