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[Doc]: fix typos in .md files (including those of #23751) (#23825)

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Signed-off-by: Didier Durand <durand.didier@gmail.com>
This commit is contained in:
Didier Durand
2025-08-28 13:38:19 +02:00
committed by GitHub
parent 3462c1c522
commit d99c3a4f7b
16 changed files with 19 additions and 19 deletions
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4
docs/getting_started/installation/aws_neuron.md
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@@ -140,8 +140,8 @@ Alternatively, users can directly call the NxDI library to trace and compile you
- `NEURON_COMPILED_ARTIFACTS`: set this environment variable to point to your pre-compiled model artifacts directory to avoid
compilation time upon server initialization. If this variable is not set, the Neuron module will perform compilation and save the
artifacts under `neuron-compiled-artifacts/{unique_hash}/` sub-directory in the model path. If this environment variable is set,
but the directory does not exist, or the contents are invalid, Neuron will also fallback to a new compilation and store the artifacts
artifacts under `neuron-compiled-artifacts/{unique_hash}/` subdirectory in the model path. If this environment variable is set,
but the directory does not exist, or the contents are invalid, Neuron will also fall back to a new compilation and store the artifacts
under this specified path.
- `NEURON_CONTEXT_LENGTH_BUCKETS`: Bucket sizes for context encoding. (Only applicable to `transformers-neuronx` backend).
- `NEURON_TOKEN_GEN_BUCKETS`: Bucket sizes for token generation. (Only applicable to `transformers-neuronx` backend).

2
docs/getting_started/installation/cpu/apple.inc.md
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@@ -1,6 +1,6 @@
# --8<-- [start:installation]
vLLM has experimental support for macOS with Apple silicon. For now, users must build from source to natively run on macOS.
vLLM has experimental support for macOS with Apple Silicon. For now, users must build from source to natively run on macOS.
Currently the CPU implementation for macOS supports FP32 and FP16 datatypes.

2
docs/getting_started/installation/gpu/cuda.inc.md
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@@ -48,7 +48,7 @@ uv pip install https://github.com/vllm-project/vllm/releases/download/v${VLLM_VE
#### Install the latest code
LLM inference is a fast-evolving field, and the latest code may contain bug fixes, performance improvements, and new features that are not released yet. To allow users to try the latest code without waiting for the next release, vLLM provides wheels for Linux running on a x86 platform with CUDA 12 for every commit since `v0.5.3`.
LLM inference is a fast-evolving field, and the latest code may contain bug fixes, performance improvements, and new features that are not released yet. To allow users to try the latest code without waiting for the next release, vLLM provides wheels for Linux running on an x86 platform with CUDA 12 for every commit since `v0.5.3`.
```bash
uv pip install -U vllm \

4
docs/getting_started/installation/gpu/rocm.inc.md
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@@ -149,7 +149,7 @@ Build a docker image from <gh-file:docker/Dockerfile.rocm_base> which setup ROCm
**This step is optional as this rocm_base image is usually prebuilt and store at [Docker Hub](https://hub.docker.com/r/rocm/vllm-dev) under tag `rocm/vllm-dev:base` to speed up user experience.**
If you choose to build this rocm_base image yourself, the steps are as follows.
It is important that the user kicks off the docker build using buildkit. Either the user put DOCKER_BUILDKIT=1 as environment variable when calling docker build command, or the user needs to setup buildkit in the docker daemon configuration /etc/docker/daemon.json as follows and restart the daemon:
It is important that the user kicks off the docker build using buildkit. Either the user put DOCKER_BUILDKIT=1 as environment variable when calling docker build command, or the user needs to set up buildkit in the docker daemon configuration /etc/docker/daemon.json as follows and restart the daemon:
```json
{
@@ -170,7 +170,7 @@ DOCKER_BUILDKIT=1 docker build \
#### Build an image with vLLM
First, build a docker image from <gh-file:docker/Dockerfile.rocm> and launch a docker container from the image.
It is important that the user kicks off the docker build using buildkit. Either the user put `DOCKER_BUILDKIT=1` as environment variable when calling docker build command, or the user needs to setup buildkit in the docker daemon configuration /etc/docker/daemon.json as follows and restart the daemon:
It is important that the user kicks off the docker build using buildkit. Either the user put `DOCKER_BUILDKIT=1` as environment variable when calling docker build command, or the user needs to set up buildkit in the docker daemon configuration /etc/docker/daemon.json as follows and restart the daemon:
```bash
{