A high-throughput and memory-efficient inference and serving engine for LLMs
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Synced Nov 15, 13:30 UTC
[Doc] Fix wrong github link in LMCache examples (#17274)
Signed-off-by: KuntaiDu <kuntai@uchicago.edu>
Kuntai Du committed
Apr 27, 2025 at 20:09 UTC
9053d0b134e574767f661df521decffd796ff440
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examples/lmcache/README.md
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@@ -8,8 +8,8 @@ This example demonstrates how to run LMCache with disaggregated prefill using NI
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### Prerequisites
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-- Install [LMCache](https://github.com/ai-dynamo/lmcache)
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-- Install [NIXL](https://github.com/ai-dynamo/nixl)
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+- Install [LMCache](https://github.com/LMCache/LMCache). You can simply run `pip install lmcache`.
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+- Install [NIXL](https://github.com/ai-dynamo/nixl).
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- At least 2 GPUs
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- Valid Hugging Face token (HF_TOKEN) for Llama 3.1 8B Instruct.
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