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chore : correct typos [no ci] (#20041)

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* fix(docs): correct typos found during code review

Non-functional changes only:
- Fixed minor spelling mistakes in comments
- Corrected typos in user-facing strings
- No variables, logic, or functional code was modified.

Signed-off-by: Marcel Petrick <mail@marcelpetrick.it>

* Update docs/backend/CANN.md

Co-authored-by: Aaron Teo <taronaeo@gmail.com>

* Revert "Auxiliary commit to revert individual files from 846d1c301281178efbc6ce6060ad34c1ebe45af8"

This reverts commit 02fcf0c7db661d5ff3eff96b2b2db9fdb7213256.

* Update tests/test-backend-ops.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Update tests/test-backend-ops.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

---------

Signed-off-by: Marcel Petrick <mail@marcelpetrick.it>
Co-authored-by: Aaron Teo <taronaeo@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
This commit is contained in:
Marcel Petrick
2026-03-05 08:50:21 +01:00
committed by GitHub
parent 7a99dc85e2
commit 92f7da00b4
81 changed files with 160 additions and 160 deletions
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docs/backend/CANN.md
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@@ -20,7 +20,7 @@
**Llama.cpp + CANN**
The llama.cpp CANN backend is designed to support Ascend NPU. It utilize the ability of AscendC and ACLNN which are intergrated to CANN Toolkit and kernels to using Ascend NPU directly.
The llama.cpp CANN backend is designed to support Ascend NPU. It utilize the ability of AscendC and ACLNN which are integrated to CANN Toolkit and kernels to using Ascend NPU directly.
## News
@@ -210,7 +210,7 @@ docker run --name llamacpp --device /dev/davinci0 --device /dev/davinci_manager
# and install driver.
sudo sh Ascend-hdk-910b-npu-firmware_x.x.x.x.X.run --full
```
If the following messaage appers, firmware is installed successfully.
If the following message appears, firmware is installed successfully.
```sh
Firmware package installed successfully!
```
docs/backend/SYCL.md
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@@ -708,7 +708,7 @@ use 1 SYCL GPUs: [0] with Max compute units:512
- Remove **build** folder or try a clean-build.
- I can **not** see `[ext_oneapi_level_zero:gpu]` afer installing the GPU driver on Linux.
- I can **not** see `[ext_oneapi_level_zero:gpu]` after installing the GPU driver on Linux.
Please double-check with `sudo sycl-ls`.
docs/backend/snapdragon/README.md
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@@ -116,7 +116,7 @@ Llama-3.2-1B-Instruct-Q4_0.gguf: 1 file pushed, 0 skipped. 38.3 MB/s (773025920
### Windows
All artifacts are already installed in the `pkg-snapdragon` folder.
To run, adapt below instructions to use Powershell scrits in `scripts/snapdragon/windows`.
To run, adapt below instructions to use Powershell scripts in `scripts/snapdragon/windows`.
## How to Run
docs/backend/snapdragon/windows.md
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@@ -144,7 +144,7 @@ Once the build is complete HTP ops libraries will be installed like this
-a---- 1/22/2026 6:01 PM 4139 libggml-htp.cat
```
The .cat file, the signature and proper certicate installation can be verified with
The .cat file, the signature and proper certificate installation can be verified with
```
> signtool.exe verify /v /pa .\pkg-snapdragon\lib\libggml-htp.cat
docs/build.md
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@@ -595,7 +595,7 @@ You can verify that KleidiAI is being used by running
```bash
./build/bin/llama-cli -m PATH_TO_MODEL -p "What is a car?"
```
If KleidiAI is enabled, the ouput will contain a line similar to:
If KleidiAI is enabled, the output will contain a line similar to:
```
load_tensors: CPU_KLEIDIAI model buffer size = 3474.00 MiB
```
@@ -699,7 +699,7 @@ To read documentation for how to build on Android, [click here](./android.md)
## WebGPU [In Progress]
The WebGPU backend relies on [Dawn](https://dawn.googlesource.com/dawn). Follow the instructions [here](https://dawn.googlesource.com/dawn/+/refs/heads/main/docs/quickstart-cmake.md) to install Dawn locally so that llama.cpp can find it using CMake. The currrent implementation is up-to-date with Dawn commit `bed1a61`.
The WebGPU backend relies on [Dawn](https://dawn.googlesource.com/dawn). Follow the instructions [here](https://dawn.googlesource.com/dawn/+/refs/heads/main/docs/quickstart-cmake.md) to install Dawn locally so that llama.cpp can find it using CMake. The current implementation is up-to-date with Dawn commit `bed1a61`.
In the llama.cpp directory, build with CMake:
docs/multimodal/MobileVLM.md
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@@ -281,7 +281,7 @@ llama_print_timings: total time = 5990.25 ms / 202 tokens
Just the same as above.
**ouput**
**output**
```sh
encode_image_with_clip: image embedding created: 144 tokens
@@ -305,7 +305,7 @@ llama_print_timings: total time = 15513.95 ms / 412 tokens
## Run on Intel(R) Core(TM) Ultra7 115H
### operation system
Windows11
### comiple
### compile
```sh
make -j32
```