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Home / v1.56
Name Modified Size InfoDownloads / Week
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koboldcpp-linux-x64-nocuda 2024-01-27 48.4 MB
koboldcpp-linux-x64 2024-01-27 374.0 MB
koboldcpp.exe 2024-01-27 295.6 MB
koboldcpp_nocuda.exe 2024-01-27 29.6 MB
koboldcpp-1.56 source code.tar.gz 2024-01-27 17.1 MB
koboldcpp-1.56 source code.zip 2024-01-27 17.3 MB
README.md 2024-01-27 2.4 kB
Totals: 7 Items   782.0 MB 0

koboldcpp-1.56

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  • NEW: Added early support for new Vulkan GPU backend by @0cc4m. You can try it out with the command --usevulkan (gpu id) or via the GUI launcher. Now included with the Windows and Linux prebuilt binaries. (Note: Mixtral on Vulkan not fully supported)
  • Updated and merged the new GGML backend rework from upstream. This update includes many extensive fixes, improvements and changes across over a hundred commits. Support for earlier non-gguf models has been preserved via a fossilized earlier version of the library. Please open an issue if you encounter problems. The Wiki and Readme have been updated too.
  • Added support for setting dynatemp_exponent, previously was defaulted at 1.0. Support added over API and in Lite.
  • Fixed issues with Linux CUDA on Pascal, added more flags to handle conda and colab builds correctly.
  • Added support for Old CPU fallbacks (NoAVX2 and Failsafe modes) in build targets in the Linux prebuilt binary (and koboldcpp.sh)
  • Added missing 48k context option, fixed clearing file selection, better abort handling support, fixed aarch64 termux builds, various other fixes.
  • Updated Kobold Lite with many improvements and new features:
  • NEW: Added XTTS API Server support (Local AI powered text-to-speech).
  • Added option to let AI impersonate you for a turn in a chat.
  • HD image generation options.
  • Added popup-on-complete browser notification options.
  • Improved DynaTemp wizard, added options to set exponent
  • Bugfixes, padding adjustments, A1111 parameter fixes, image color fixes for invert color mode.

To use, download and run the koboldcpp.exe, which is a one-file pyinstaller. If you don't need CUDA, you can use koboldcpp_nocuda.exe which is much smaller. If you're using AMD, you can try koboldcpp_rocm at YellowRoseCx's fork here

Run it from the command line with the desired launch parameters (see --help), or manually select the model in the GUI. and then once loaded, you can connect like this (or use the full koboldai client): http://localhost:5001

For more information, be sure to run the program from command line with the --help flag.

Source: README.md, updated 2024-01-27