[Docs] Sync docs_new with legacy docs and update migration redirects (#23337)
Co-authored-by: Mingyi <wisclmy0611@gmail.com>
This commit is contained in:
zijiexia
@@ -26,7 +26,7 @@ To use DeepSeek-Math-V2, you must agree to DeepSeek's Community License. See [LI
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## 2. SGLang Installation
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -28,7 +28,7 @@ For more details, please refer to the [official DeepSeek-OCR-2 repository](https
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## 2. SGLang Installation
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -24,7 +24,7 @@ For more details, please refer to the [official DeepSeek-OCR repository](https:/
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## 2. SGLang Installation
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -30,7 +30,7 @@ For more details, please refer to the [official DeepSeek-R1 repository](https://
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## 2. SGLang Installation
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -20,7 +20,7 @@ Key highlights include:
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -16,7 +16,7 @@ metatags:
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -22,7 +22,7 @@ The DeepSeek-V3.2 series includes three model variants, each optimized for diffe
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -21,7 +21,7 @@ ERNIE-4.5 delivers advanced features as below:
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -2,7 +2,6 @@
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title: Chroma-1.0
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metatags:
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description: "Deploy Chroma-1.0 end-to-end speech conversation model with SGLang - real-time speech generation, voice cloning, and speech reasoning."
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tag: NEW
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---
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## 1. Model Introduction
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@@ -28,7 +28,7 @@ Please refer to the [official GLM-4.5 model card](https://huggingface.co/zai-org
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -22,7 +22,7 @@ GLM-4.5V introduces several key features:
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -22,7 +22,7 @@ For more details, please refer to the [official GLM-4.6 documentation](https://d
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -54,7 +54,7 @@ sudo apt install ffmpeg
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- Want to use the latest development features
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- Participate in SGLang project development
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For general installation instructions, you can also refer to the [official SGLang installation guide](../../../docs/get-started/installation).
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For general installation instructions, you can also refer to the [official SGLang installation guide](../../../docs/get-started/install).
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## 3. Model Deployment
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@@ -37,7 +37,7 @@ Please refer to the [official GLM-4.7-Flash model card](https://huggingface.co/z
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -38,7 +38,7 @@ Please refer to the [official GLM-4.7 model card](https://huggingface.co/zai-org
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -16,7 +16,7 @@ tag: NEW
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## 2. SGLang Installation
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -2,7 +2,6 @@
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title: GLM-5
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metatags:
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description: "Deploy GLM-5 with SGLang on NVIDIA H100/H200/B200 and AMD MI300X/MI325X/MI355X — state-of-the-art reasoning, enhanced coding, and robust tool calling capabilities."
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tag: NEW
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---
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## 1. Model Introduction
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@@ -28,7 +27,7 @@ With advances in both pre-training (28.5T tokens) and post-training via [slime](
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## 2. SGLang Installation
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -31,7 +31,7 @@ Please refer to the [official Glyph model card](https://huggingface.co/zai-org/G
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -25,7 +25,7 @@ For more details, please refer to the [official GLM-OCR model card](https://hugg
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -2,6 +2,7 @@
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title: Gemma 4
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metatags:
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description: "Deploy Gemma 4 with SGLang - Google's next-generation open models with MoE variants and multimodal support for text, vision, and audio."
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tag: NEW
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---
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import { Gemma4Deployment } from '/src/snippets/autoregressive/gemma4-deployment.jsx';
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@@ -79,7 +80,7 @@ docker pull lmsysorg/sglang:dev-gemma4 # CUDA 12.9
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docker pull lmsysorg/sglang:dev-cu13-gemma4 # CUDA 13
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```
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For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/installation).
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For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/install).
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## 3. Model Deployment
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@@ -2,7 +2,6 @@
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title: LLaDA 2.1
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metatags:
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description: "Deploy LLaDA 2.1 with SGLang - large-scale discrete diffusion language model with parallel token generation, iterative denoising, MoE architecture, and reinforcement learning for reasoning."
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tag: NEW
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---
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import { LLaDA21Deployment } from '/src/snippets/autoregressive/llada-21-deployment.jsx';
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@@ -64,7 +63,7 @@ Apache 2.0. Please refer to the [official LLaDA2.X repository](https://github.co
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -2,7 +2,6 @@
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title: Ling-2.5-1T
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metatags:
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description: "Deploy Ling-2.5-1T with SGLang - 1T parameter MoE model with 63B active parameters, trillion-scale context length up to 1M tokens, and agentic tool calling capabilities."
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tag: NEW
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---
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## 1. Model Introduction
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@@ -35,9 +34,9 @@ docker pull lmsysorg/sglang:nightly-dev-20260213-a0ebaa64
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docker pull lmsysorg/sglang:nightly-dev-cu13-20260213-a0ebaa64
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```
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For other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/installation).
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For other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/install).
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Ling-2.5-1T is also supported via the **nightly PyPI builds**. See the [SGLang Installation (PyPI)](../../../docs/get-started/installation) guide for setup instructions.
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Ling-2.5-1T is also supported via the **nightly PyPI builds**. See the [SGLang Installation (PyPI)](../../../docs/get-started/install) guide for setup instructions.
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## 3. Model Deployment
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@@ -2,7 +2,6 @@
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title: Ring-2.5-1T
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metatags:
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description: "Deploy Ring-2.5-1T with SGLang - world's first open-source 1T parameter reasoning model with hybrid linear attention, deep reasoning, and agentic tool calling capabilities."
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tag: NEW
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---
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## 1. Model Introduction
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@@ -42,7 +41,7 @@ docker pull lmsysorg/sglang:v0.5.9-rocm700-mi30x
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docker pull lmsysorg/sglang:v0.5.9-rocm700-mi35x
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```
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For other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/installation).
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For other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/install).
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## 3. Model Deployment
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@@ -20,7 +20,7 @@ For further details, please refer to the [Llama 3.1 blog](https://ai.meta.com/bl
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -22,7 +22,7 @@ For more details, please refer to the [official Llama models repository](https:/
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## 2. SGLang Installation
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -27,7 +27,7 @@ For more details, please refer to the official llama4 Repository:https://www.lla
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
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Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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## 3. Model Deployment
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@@ -2,7 +2,6 @@
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title: MiniMax-M2.5
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metatags:
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description: "Deploy MiniMax-M2.5 with SGLang - community contribution guide for MiniMax M2.5 model deployment."
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tag: NEW
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---
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import { MiniMaxM25Deployment } from '/src/snippets/autoregressive/minimax-m25-deployment.jsx';
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@@ -24,7 +23,7 @@ For more details, please refer to the [official MiniMax-M2.5 announcement](https
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
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**For AMD MI300X/MI325X/MI355X GPUs:**
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@@ -24,7 +24,7 @@ For more details, see the [official MiniMax-M2.7 blog post](https://www.minimax.
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SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
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**Docker Images by Hardware Platform:**
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@@ -26,7 +26,7 @@ For more details, please refer to the [official Minimax GitHub Repository](https
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions. The AMD environment is currently available in SGLang via Docker image install.
|
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Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions. The AMD environment is currently available in SGLang via Docker image install.
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### 2.1 AMD Docker
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#### 2.1.1 Launch docker
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@@ -35,7 +35,7 @@ For enterprises requiring specialized capabilities (increased context, domain-sp
|
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|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
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|
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<Warning title="Transformers version requirement">
|
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Devstral 2 requires a recent `transformers`. Please verify `transformers >= 5.0.0.rc`:
|
||||
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||||
@@ -23,7 +23,7 @@ For further details, please refer to the [official documentation](https://github
|
||||
|
||||
## 2. SGLang Installation
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -43,10 +43,10 @@ With its multimodal capabilities, efficient MoE architecture, and flexible mode
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
<Info>
|
||||
Mistral Small 4 support landed in [sgl-project/sglang#20708](https://github.com/sgl-project/sglang/pull/20708) and has been merged into `main`. A model-specific Docker image is no longer required. Use the standard SGLang installation methods from the [official installation guide](../../../docs/get-started/installation).
|
||||
Mistral Small 4 support landed in [sgl-project/sglang#20708](https://github.com/sgl-project/sglang/pull/20708) and has been merged into `main`. A model-specific Docker image is no longer required. Use the standard SGLang installation methods from the [official installation guide](../../../docs/get-started/install).
|
||||
</Info>
|
||||
|
||||
---
|
||||
|
||||
@@ -23,7 +23,7 @@ For details, see [official documentation](https://huggingface.co/moonshotai/Kimi
|
||||
|
||||
## 2. SGLang Installation
|
||||
|
||||
Refer to the [official SGLang installation guide](../../../docs/get-started/installation).
|
||||
Refer to the [official SGLang installation guide](../../../docs/get-started/install).
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -72,7 +72,7 @@ For details, see [official documentation](https://huggingface.co/moonshotai/Kimi
|
||||
|
||||
## 2. SGLang Installation
|
||||
|
||||
Refer to the [official SGLang installation guide](../../../docs/get-started/installation).
|
||||
Refer to the [official SGLang installation guide](../../../docs/get-started/install).
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -20,7 +20,7 @@ For details, see [official documentation](https://github.com/MoonshotAI/Kimi-K2)
|
||||
|
||||
## 2. SGLang Installation
|
||||
|
||||
Refer to the [official SGLang installation guide](../../../docs/get-started/installation).
|
||||
Refer to the [official SGLang installation guide](../../../docs/get-started/install).
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -24,7 +24,7 @@ For more details, please refer to the [official Kimi Linear GitHub Repository]:
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -20,7 +20,7 @@ At a high level:
|
||||
|
||||
## 2. SGLang Installation
|
||||
|
||||
Refer to the [official SGLang installation guide](../../../docs/get-started/installation), or install nightly wheel through:
|
||||
Refer to the [official SGLang installation guide](../../../docs/get-started/install), or install nightly wheel through:
|
||||
```bash Command
|
||||
uv pip install sglang==0.5.6.post3.dev1278+gad1b4e472 --extra-index-url https://sgl-project.github.io/whl/nightly/
|
||||
```
|
||||
|
||||
@@ -31,7 +31,7 @@ uv pip install 'git+https://github.com/sgl-project/sglang.git#subdirectory=pytho
|
||||
docker pull lmsysorg/sglang:nightly-dev-20260310-0fd9a57d
|
||||
```
|
||||
|
||||
For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/installation).
|
||||
For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/install).
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -23,7 +23,7 @@ GPT-OSS introduces several groundbreaking innovations:
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
## 3.Model Deployment
|
||||
|
||||
|
||||
@@ -27,7 +27,7 @@ For more details, please refer to the [official Qwen2.5-VL GitHub Repository](ht
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -24,7 +24,7 @@ For more details, please refer to the [Qwen3-Coder-Next model card](https://hugg
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
**Note:** Qwen3-Coder-Next requires SGLang v0.5.8 or later.
|
||||
|
||||
|
||||
@@ -26,7 +26,7 @@ For more details, please refer to the [official Qwen3-Coder GitHub Repository](h
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -30,7 +30,7 @@ For more details, please refer to the [official Qwen3-Next blog](https://qwen.ai
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -24,7 +24,7 @@ For more details, please refer to the [official Qwen3-VL GitHub Repository](http
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -104,7 +104,7 @@ docker pull lmsysorg/sglang:v0.5.9-rocm720-mi30x
|
||||
docker pull lmsysorg/sglang:v0.5.9-rocm720-mi35x
|
||||
```
|
||||
|
||||
For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/installation).
|
||||
For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/install).
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -61,7 +61,7 @@ uv pip install 'git+https://github.com/sgl-project/sglang.git#subdirectory=pytho
|
||||
docker pull lmsysorg/sglang:latest
|
||||
```
|
||||
|
||||
For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/installation).
|
||||
For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/install).
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -24,7 +24,7 @@ For more details, please refer to the [official Qwen3 GitHub Repository](https:/
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -2,7 +2,6 @@
|
||||
title: Step3-VL-10B
|
||||
metatags:
|
||||
description: "Deploy Step3-VL-10B multimodal model with SGLang - compact 10B dense model with frontier-level vision understanding, complex reasoning, and tool calling capabilities."
|
||||
tag: NEW
|
||||
---
|
||||
|
||||
import { Step3VL10BDeployment } from '/src/snippets/autoregressive/step-3vl-10b-deployment.jsx';
|
||||
@@ -24,7 +23,7 @@ For more details, please refer to the [Step3-VL-10B model card on Hugging Face](
|
||||
|
||||
SGLang offers multiple installation methods. You can choose the most suitable installation method based on your hardware platform and requirements.
|
||||
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/installation) for installation instructions.
|
||||
Please refer to the [official SGLang installation guide](../../../docs/get-started/install) for installation instructions.
|
||||
|
||||
## 3. Model Deployment
|
||||
|
||||
|
||||
@@ -2,7 +2,6 @@
|
||||
title: Step-3.5
|
||||
metatags:
|
||||
description: "Deploy Step-3.5 reasoning engine with SGLang. "
|
||||
tag: NEW
|
||||
---
|
||||
|
||||
import { Step35Deployment } from '/src/snippets/autoregressive/step-35-deployment.jsx';
|
||||
|
||||
@@ -32,7 +32,7 @@ Qwen-Image is a text-to-image model. The recommended launch configurations vary
|
||||
|
||||
### 3.2 Configuration Tips
|
||||
|
||||
Current supported optimization all listed [here](../../../docs/sglang-diffusion/attention-backends#platform-support-matrix).
|
||||
Current supported optimization all listed [here](../../../docs/sglang-diffusion/attention_backends#platform-support-matrix).
|
||||
|
||||
- `--vae-path`: Path to a custom VAE model or HuggingFace model ID (e.g., fal/FLUX.2-Tiny-AutoEncoder). If not specified, the VAE will be loaded from the main model path.
|
||||
- `--num-gpus`: Number of GPUs to use
|
||||
@@ -45,7 +45,7 @@ Current supported optimization all listed [here](../../../docs/sglang-diffusion/
|
||||
|
||||
## 4. API Usage
|
||||
|
||||
For complete API documentation, please refer to the [official API usage guide](../../../docs/sglang-diffusion/api/openai-api).
|
||||
For complete API documentation, please refer to the [official API usage guide](../../../docs/sglang-diffusion/api/openai_api).
|
||||
|
||||
### 4.1 Generate an Image
|
||||
|
||||
@@ -72,7 +72,7 @@ with open("output.png", "wb") as f:
|
||||
|
||||
#### 4.2.1 Cache-DiT Acceleration
|
||||
|
||||
SGLang integrates [Cache-DiT](https://github.com/vipshop/cache-dit), a caching acceleration engine for Diffusion Transformers (DiT), to achieve up to 7.4x inference speedup with minimal quality loss. You can set `SGLANG_CACHE_DIT_ENABLED=True` to enable it. For more details, please refer to the SGLang Cache-DiT [documentation](../../../docs/sglang-diffusion/cache-dit).
|
||||
SGLang integrates [Cache-DiT](https://github.com/vipshop/cache-dit), a caching acceleration engine for Diffusion Transformers (DiT), to achieve up to 7.4x inference speedup with minimal quality loss. You can set `SGLANG_CACHE_DIT_ENABLED=True` to enable it. For more details, please refer to the SGLang Cache-DiT [documentation](../../../docs/sglang-diffusion/cache_dit).
|
||||
|
||||
**Basic Usage**
|
||||
|
||||
|
||||
@@ -43,7 +43,7 @@ The Wan2.1 series offers models in multiple sizes and resolutions, optimized for
|
||||
|
||||
### 3.2 Configuration Tips
|
||||
|
||||
Current supported optimization options are listed in the [SGLang diffusion support matrix](../../../docs/sglang-diffusion/attention-backends#platform-support-matrix).
|
||||
Current supported optimization options are listed in the [SGLang diffusion support matrix](../../../docs/sglang-diffusion/attention_backends#platform-support-matrix).
|
||||
|
||||
- `--vae-path`: Path to a custom VAE model or HuggingFace model ID. If not specified, the VAE will be loaded from the main model path.
|
||||
- `--num-gpus {NUM_GPUS}`: Number of GPUs to use.
|
||||
@@ -58,7 +58,7 @@ Current supported optimization options are listed in the [SGLang diffusion suppo
|
||||
### 4.1 Basic Usage
|
||||
|
||||
For more API usage and request examples, please refer to:
|
||||
[SGLang Diffusion OpenAI API](../../../docs/sglang-diffusion/api/openai-api)
|
||||
[SGLang Diffusion OpenAI API](../../../docs/sglang-diffusion/api/openai_api)
|
||||
|
||||
#### 4.1.1 Launch a server and then send requests
|
||||
|
||||
@@ -104,7 +104,7 @@ sglang generate "${SERVER_ARGS[@]}" "${SAMPLING_ARGS[@]}"
|
||||
|
||||
#### 4.2.1 Cache-DiT Acceleration
|
||||
|
||||
SGLang integrates [Cache-DiT](https://github.com/vipshop/cache-dit), a caching acceleration engine for Diffusion Transformers (DiT), to achieve significant inference speedups with minimal quality loss. You can set `SGLANG_CACHE_DIT_ENABLED=True` to enable it. For more details, please refer to the SGLang Cache-DiT [documentation](../../../docs/sglang-diffusion/cache-dit).
|
||||
SGLang integrates [Cache-DiT](https://github.com/vipshop/cache-dit), a caching acceleration engine for Diffusion Transformers (DiT), to achieve significant inference speedups with minimal quality loss. You can set `SGLANG_CACHE_DIT_ENABLED=True` to enable it. For more details, please refer to the SGLang Cache-DiT [documentation](../../../docs/sglang-diffusion/cache_dit).
|
||||
|
||||
**Basic Usage**
|
||||
|
||||
|
||||
@@ -149,7 +149,7 @@ Each recipe provides step-by-step instructions to help you quickly implement SGL
|
||||
|
||||
## Reference
|
||||
|
||||
- [Installation (PyPI)](../docs/get-started/installation) - Install SGLang via pip or uv (stable and nightly)
|
||||
- [Installation (PyPI)](../docs/get-started/install) - Install SGLang via pip or uv (stable and nightly)
|
||||
- [Server arguments](./base/reference/server_arguments) - Understanding all the arguments
|
||||
|
||||
## 🚀 Quick Start
|
||||
|
||||
Reference in New Issue
Block a user