EngineX/xc-llm-ascend
3
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

[Doc] Update doc url link (#5781)

Browse Source 
Drop `dev` suffix for doc url.
Rename url to `https://docs.vllm.ai/projects/ascend`

- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2026-01-12 11:21:31 +08:00
committed by GitHub
parent 297f6deb09
commit 354ee3b330
16 changed files with 83 additions and 83 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
docs/source/faqs.md
View File

@@ -67,7 +67,7 @@ docker images | grep vllm-ascend
### 3. What models does vllm-ascend supports?
Find more details [<u>here</u>](https://vllm-ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_models.html).
Find more details [<u>here</u>](https://docs.vllm.ai/projects/ascend/en/latest/user_guide/support_matrix/supported_models.html).
### 4. How to get in touch with our community?
@@ -80,7 +80,7 @@ There are many channels that you can communicate with our community developers /
### 5. What features does vllm-ascend V1 supports?
Find more details [<u>here</u>](https://vllm-ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_features.html).
Find more details [<u>here</u>](https://docs.vllm.ai/projects/ascend/en/latest/user_guide/support_matrix/supported_features.html).
### 6. How to solve the problem of "Failed to infer device type" or "libatb.so: cannot open shared object file"?
@@ -104,7 +104,7 @@ vllm-ascend is a hardware plugin for vLLM. Basically, the version of vllm-ascend
### 8. Does vllm-ascend support Prefill Disaggregation feature?
Yes, vllm-ascend supports Prefill Disaggregation feature with Mooncake backend. Take [official tutorial](https://vllm-ascend.readthedocs.io/en/latest/tutorials/pd_disaggregation_mooncake_multi_node.html) for example.
Yes, vllm-ascend supports Prefill Disaggregation feature with Mooncake backend. Take [official tutorial](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/pd_disaggregation_mooncake_multi_node.html) for example.
### 9. Does vllm-ascend support quantization method?
@@ -112,13 +112,13 @@ Currently, w8a8, w4a8 and w4a4 quantization methods are already supported by vll
### 10. How to run a W8A8 DeepSeek model?
Follow the [inference tutorial](https://vllm-ascend.readthedocs.io/en/latest/tutorials/multi_node.html) and replace the model with DeepSeek.
Follow the [inference tutorial](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/multi_node.html) and replace the model with DeepSeek.
### 11. How is vllm-ascend tested?
vllm-ascend is tested in three aspects, functions, performance, and accuracy.
- **Functional test**: We added CI, including part of vllm's native unit tests and vllm-ascend's own unit tests. On vllm-ascend's test, we test basic functionalities, popular model availability, and [supported features](https://vllm-ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_features.html) through E2E test.
- **Functional test**: We added CI, including part of vllm's native unit tests and vllm-ascend's own unit tests. On vllm-ascend's test, we test basic functionalities, popular model availability, and [supported features](https://docs.vllm.ai/projects/ascend/en/latest/user_guide/support_matrix/supported_features.html) through E2E test.
- **Performance test**: We provide [benchmark](https://github.com/vllm-project/vllm-ascend/tree/main/benchmarks) tools for E2E performance benchmark, which can be easily re-routed locally. We will publish a perf website to show the performance test results for each pull request.