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Replies: 2 comments 4 replies
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Sequentially it can for sure, if you have spare ram smartcache will keep context sessions cached better between them. In parralel thats more experimental and limited to samplers and things llamacpp can also do, thar would be continuos-batching. |
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@alex-ie it already does it automatically as a queue by default. If you mean getting all instances to reply at the same time, try setting |
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I wonder if
kcppcan be used in a manner of llama-server? I mean to have several conversations / chats that share same instance and same GPU VRAM allocation of model weights but its own KV cache (if I misunderstand how llama-server works - please correct me)? I do not recall such feature of kcpp, but maybe I have missed something.If no such, how easily could it be added? TIA
P.S. I used to run LLMs on CPU and just did
--usemmapto run several instances of kcpp. But now I use GPU to help with prefill / prompt processing and even with-ngl 1I cannot fit many in VRAM.All reactions