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[Doc] fix the nit in docs (#6826)

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Refresh the doc, fix the nit in the docs

- vLLM version: v0.15.0
- vLLM main:
83b47f67b1

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2026-02-27 11:50:27 +08:00
committed by GitHub
parent 981d803cb7
commit a95c0b8b82
30 changed files with 145 additions and 118 deletions
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14
docs/source/tutorials/models/GLM5.md
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@@ -2,15 +2,15 @@
## Introduction
[GLM-5](https://huggingface.co/zai-org/GLM-5)use a Mixture-of-Experts (MoE) architecture and targeting at complex systems engineering and long-horizon agentic tasks.
[GLM-5](https://huggingface.co/zai-org/GLM-5) use a Mixture-of-Experts (MoE) architecture and targeting at complex systems engineering and long-horizon agentic tasks.
This document will show the main verification steps of the model, including supported features, feature configuration, environment preparation, single-node and multi-node deployment, accuracy and performance evaluation.
## Supported Features
Refer to [supported features](https://docs.vllm.ai/projects/ascend/en/latest/user_guide/support_matrix/supported_models.html)to get the model's supported feature matrix.
Refer to [supported features](../../user_guide/support_matrix/supported_models.md) to get the model's supported feature matrix.
Refer to [feature guide](https://docs.vllm.ai/projects/ascend/en/latest/user_guide/support_matrix/supported_features.html) to get the feature's configuration.
Refer to [feature guide](../../user_guide/feature_guide/index.md) to get the feature's configuration.
## Environment Preparation
@@ -241,7 +241,7 @@ The parameters are explained as follows:
### Multi-node Deployment
If you want to deploy multi-node environment, you need to verify multi-node communication according to [verify multi-node communication environment](https://docs.vllm.ai/projects/ascend/en/latest/installation.html#verify-multi-node-communication).
If you want to deploy multi-node environment, you need to verify multi-node communication according to [verify multi-node communication environment](../../installation.md#verify-multi-node-communication).
:::::{tab-set}
:sync-group: install
@@ -450,7 +450,7 @@ vllm serve /root/.cache/modelscope/hub/models/vllm-ascend/GLM-5-w4a8 \
::::
:::::
- For bf16 weight, use this script on each node to enable [Multi Token Prediction (MTP)](https://docs.vllm.ai/projects/ascend/en/latest/user_guide/feature_guide/Multi_Token_Prediction.html).
- For bf16 weight, use this script on each node to enable [Multi Token Prediction (MTP)](../../user_guide/feature_guide/Multi_Token_Prediction.md).
```shell
python adjust_weight.py "path_of_bf16_weight"
@@ -518,7 +518,7 @@ Here are two accuracy evaluation methods.
### Using AISBench
1. Refer to [Using AISBench](https://docs.vllm.ai/projects/ascend/en/latest/developer_guide/evaluation/using_ais_bench.html) for details.
1. Refer to [Using AISBench](../../developer_guide/evaluation/using_ais_bench.md) for details.
2. After execution, you can get the result.
@@ -530,7 +530,7 @@ Not test yet.
### Using AISBench
Refer to [Using AISBench for performance evaluation](https://docs.vllm.ai/projects/ascend/en/latest/developer_guide/evaluation/using_ais_bench.html#execute-performance-evaluation) for details.
Refer to [Using AISBench for performance evaluation](../../developer_guide/evaluation/using_ais_bench.md#execute-performance-evaluation) for details.
### Using vLLM Benchmark