A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 12, 02:15 UTC
[GPU Backend] [Doc]: Remove duplicate statements on missing GPU wheels. (#29962)
Signed-off-by: Ioana Ghiban <ioana.ghiban@arm.com>
ioana ghiban committed
Dec 3, 2025 at 13:56 UTC
15b1511a15dfb1d56048847da755213632c07b29
2 files changed
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docs/getting_started/installation/gpu.rocm.inc.md
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@@ -5,9 +5,6 @@ vLLM supports AMD GPUs with ROCm 6.3 or above, and torch 2.8.0 and above.
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!!! tip
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[Docker](#set-up-using-docker) is the recommended way to use vLLM on ROCm.
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-!!! warning
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- There are no pre-built wheels for this device, so you must either use the pre-built Docker image or build vLLM from source.
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-
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# --8<-- [end:installation]
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# --8<-- [start:requirements]
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docs/getting_started/installation/gpu.xpu.inc.md
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@@ -2,9 +2,6 @@
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vLLM initially supports basic model inference and serving on Intel GPU platform.
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-!!! warning
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- There are no pre-built wheels for this device, so you need build vLLM from source. Or you can use pre-built images which are based on vLLM released versions.
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-
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# --8<-- [end:installation]
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# --8<-- [start:requirements]
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