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[Doc]: fixing typos to improve docs (#24480)

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Signed-off-by: Didier Durand <durand.didier@gmail.com>
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Didier Durand
2025-09-09 08:06:04 +02:00
committed by GitHub
parent 1823a00d67
commit 46876dff32
9 changed files with 12 additions and 12 deletions
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docs/features/tool_calling.md
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@@ -169,7 +169,7 @@ All Llama 3.1, 3.2 and 4 models should be supported.
The tool calling that is supported is the [JSON-based tool calling](https://llama.meta.com/docs/model-cards-and-prompt-formats/llama3_1/#json-based-tool-calling). For [pythonic tool calling](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/text_prompt_format.md#zero-shot-function-calling) introduced by the Llama-3.2 models, see the `pythonic` tool parser below. As for Llama 4 models, it is recommended to use the `llama4_pythonic` tool parser.
Other tool calling formats like the built in python tool calling or custom tool calling are not supported.
Other tool calling formats like the built-in python tool calling or custom tool calling are not supported.
Known issues:

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docs/getting_started/installation/gpu/rocm.inc.md
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@@ -119,7 +119,7 @@ Currently, there are no pre-built ROCm wheels.
This may take 5-10 minutes. Currently, `pip install .` does not work for ROCm installation.
!!! tip
- Triton flash attention is used by default. For benchmarking purposes, it is recommended to run a warm up step before collecting perf numbers.
- Triton flash attention is used by default. For benchmarking purposes, it is recommended to run a warm-up step before collecting perf numbers.
- Triton flash attention does not currently support sliding window attention. If using half precision, please use CK flash-attention for sliding window support.
- To use CK flash-attention or PyTorch naive attention, please use this flag `export VLLM_USE_TRITON_FLASH_ATTN=0` to turn off triton flash attention.
- The ROCm version of PyTorch, ideally, should match the ROCm driver version.