[Docs] Add Falcon H1, Hunyuan-Large, Qwen3-Omni support and update Diffusion usage (#17888)

Co-authored-by: Rishitshivam <164783543+Rishitshivam@users.noreply.github.com>
Co-authored-by: Ratish P <114130421+Ratish1@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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docs/platforms/ascend_npu_support.rst

@@ -8,5 +8,6 @@ Ascend NPUs
    ascend_npu_support_models.md
    ascend_npu_deepseek_example.md
    ascend_npu_qwen3_examples.md
+   mindspore_backend.md
    ascend_contribution_guide.md
    ascend_npu_best_practice.md

docs/platforms/mindspore_backend.md

@@ -0,0 +1,151 @@
+# MindSpore Models
+
+## Introduction
+
+MindSpore is a high-performance AI framework optimized for Ascend NPUs. This doc guides users to run MindSpore models in SGLang.
+
+## Requirements
+
+MindSpore currently only supports Ascend NPU devices. Users need to first install Ascend CANN software packages.
+The CANN software packages can be downloaded from the [Ascend Official Website](https://www.hiascend.com). The recommended version is 8.3.RC2.
+
+## Supported Models
+
+Currently, the following models are supported:
+
+- **Qwen3**: Dense and MoE models
+- **DeepSeek V3/R1**
+- *More models coming soon...*
+
+## Installation
+
+> **Note**: Currently, MindSpore models are provided by an independent package `sgl-mindspore`. Support for MindSpore is built upon current SGLang support for Ascend NPU platform. Please first [install SGLang for Ascend NPU](ascend_npu.md) and then install `sgl-mindspore`:
+
+```shell
+git clone https://github.com/mindspore-lab/sgl-mindspore.git
+cd sgl-mindspore
+pip install -e .
+```
+
+
+## Run Model
+
+Current SGLang-MindSpore supports Qwen3 and DeepSeek V3/R1 models. This doc uses Qwen3-8B as an example.
+
+### Offline infer
+
+Use the following script for offline infer:
+
+```python
+import sglang as sgl
+
+# Initialize the engine with MindSpore backend
+llm = sgl.Engine(
+    model_path="/path/to/your/model",  # Local model path
+    device="npu",                      # Use NPU device
+    model_impl="mindspore",            # MindSpore implementation
+    attention_backend="ascend",        # Attention backend
+    tp_size=1,                         # Tensor parallelism size
+    dp_size=1                          # Data parallelism size
+)
+
+# Generate text
+prompts = [
+    "Hello, my name is",
+    "The capital of France is",
+    "The future of AI is"
+]
+
+sampling_params = {"temperature": 0, "top_p": 0.9}
+outputs = llm.generate(prompts, sampling_params)
+
+for prompt, output in zip(prompts, outputs):
+    print(f"Prompt: {prompt}")
+    print(f"Generated: {output['text']}")
+    print("---")
+```
+
+### Start server
+
+Launch a server with MindSpore backend:
+
+```bash
+# Basic server startup
+python3 -m sglang.launch_server \
+    --model-path /path/to/your/model \
+    --host 0.0.0.0 \
+    --device npu \
+    --model-impl mindspore \
+    --attention-backend ascend \
+    --tp-size 1 \
+    --dp-size 1
+```
+
+For distributed server with multiple nodes:
+
+```bash
+# Multi-node distributed server
+python3 -m sglang.launch_server \
+    --model-path /path/to/your/model \
+    --host 0.0.0.0 \
+    --device npu \
+    --model-impl mindspore \
+    --attention-backend ascend \
+    --dist-init-addr 127.0.0.1:29500 \
+    --nnodes 2 \
+    --node-rank 0 \
+    --tp-size 4 \
+    --dp-size 2
+```
+
+## Troubleshooting
+
+#### Debug Mode
+
+Enable sglang debug logging by log-level argument.
+
+```bash
+python3 -m sglang.launch_server \
+    --model-path /path/to/your/model \
+    --host 0.0.0.0 \
+    --device npu \
+    --model-impl mindspore \
+    --attention-backend ascend \
+    --log-level DEBUG
+```
+
+Enable mindspore info and debug logging by setting environments.
+
+```bash
+export GLOG_v=1  # INFO
+export GLOG_v=0  # DEBUG
+```
+
+#### Explicitly select devices
+
+Use the following environment variable to explicitly select the devices to use.
+
+```shell
+export ASCEND_RT_VISIBLE_DEVICES=4,5,6,7  # to set device
+```
+
+#### Some communication environment issues
+
+In case of some environment with special communication environment, users need set some environment variables.
+
+```shell
+export MS_ENABLE_LCCL=off # current not support LCCL communication mode in SGLang-MindSpore
+```
+
+#### Some dependencies of protobuf
+
+In case of some environment with special protobuf version, users need set some environment variables to avoid binary version mismatch.
+
+```shell
+export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python  # to avoid protobuf binary version mismatch
+```
+
+## Support
+For MindSpore-specific issues:
+
+- Refer to the [MindSpore documentation](https://www.mindspore.cn/)