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Releases: henk717/koboldcpp

v1.57 - Vulkan Only Pre-release

04 Feb 11:30
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This is a Vulkan Only build of the upcoming v1.57, please check on https://koboldai.org/cpp if v1.57 has already released.
If v1.57 has a formal release this build has no advantages for you.

v1.59-Ofast

25 Feb 13:43
25b89bd
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v1.59 but the makefile is changed to be OFast, for comparative testing.

1.52 - Linux

14 Dec 02:29
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v1.52

Placebo commit to maybe fix CI

1.51.1 - Linux Binary Test

09 Dec 21:31
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This is a special test release for linux, for other builds check https://koboldai.org/cpp

1.35

12 Jul 17:03
bc92bd6
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This repository is only used on special occation for compiled builds, get the latest from https://koboldai.org/cpp

Koboldcpp 1.35 build with sched_yield enabled and CUDA 11.4 for better GPU compatibiltiy
H2 update: (Still shows H on the version but newer than the henk_cuda from concedo's repository) Compiled in a VM for better dependency stability and CUDA 11.4 support.
H3 update: Same source code as the previous versions other than the version name change. Recompiled with a different psutil (from conda instead of pip) to make high priority work again.

Win7 build: Compiled without PrefetchVirtualMemory, normally Windows 7 is only supported on the Fallback backend. This is a limited edition build that has Windows 7 support on hopefully all backends (CUDA not tested) at the expense of the model loading speed.

Tools: Compilation of all the GGML conversion tools (make tools)

v1.0.3 - Windows

23 Mar 20:44
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llamacpp-for-kobold-1.0.3

  • Applied the massive refactor from the parent repo. It was a huge pain but I managed to keep the old tokenizer untouched and retained full support for the original model formats.
  • Reduced default batch sizes greatly, as large batch sizes were causing bad output and high memory usage
  • Support dynamic context lengths sent from client.
  • TavernAI is working although I wouldn't recommend it, they spam the server with multiple requests of huge contexts so you're going to have a very painful time getting responses.

To use drag and drop a compatible quantized model for llamacpp on top of the exe.

v1.0.2 - 2048 Context - Windows

21 Mar 20:53
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The original release was limited to 512 tokens, this release changes this to 2048 and uses all cores available on the system.

1.0.2 - Windows

21 Mar 19:19
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Standalone LLaMAcpp server for KoboldAI, includes KoboldAI Lite.
To use drag and drop a compatible quantized model for llamacpp on top of the exe.