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2023-04-14 21:24:16 +08:00
.github Merged upstream, fixed OSX compile errors, integrated noavx2 build into main 2023-04-12 18:08:55 +08:00
CL integrated optional (experimentl) CLBlast support 2023-04-11 23:33:44 +08:00
examples Fix whitespace, add .editorconfig, add GitHub workflow (#883) 2023-04-11 19:45:44 +00:00
lib integrated optional (experimentl) CLBlast support 2023-04-11 23:33:44 +08:00
media media : add logos and banners 2023-04-05 18:58:31 +03:00
models Make loading weights 10-100x faster 2023-03-30 12:28:25 -07:00
otherarch clean and refactor handling of flags 2023-04-12 23:25:31 +08:00
prompts add example of re-act pattern (#583) 2023-03-29 10:10:24 -05:00
spm-headers deploy : add a Package.swift for SwiftPM support (#393) 2023-03-28 19:39:01 +03:00
tests tests : free llama context at the end of the test 2023-03-28 19:51:55 +03:00
.ecrc Fix whitespace, add .editorconfig, add GitHub workflow (#883) 2023-04-11 19:45:44 +00:00
.editorconfig Fix whitespace, add .editorconfig, add GitHub workflow (#883) 2023-04-11 19:45:44 +00:00
.gitignore Merge branch 'master' into concedo 2023-04-08 17:42:09 +08:00
build.zig zig : don't link examples/common.cpp for non-example (#814) 2023-04-07 19:05:29 +03:00
cblas.h integrated optional (experimentl) CLBlast support 2023-04-11 23:33:44 +08:00
clblast.dll integrated optional (experimentl) CLBlast support 2023-04-11 23:33:44 +08:00
clblast_c.h integrated optional (experimentl) CLBlast support 2023-04-11 23:33:44 +08:00
convert-ggml-to-pth.py py: huggingface -> Hugging Face (#686) 2023-04-01 18:38:18 +02:00
convert-gpt4all-to-ggml.py py : cleanup the code 2023-03-31 10:32:01 +02:00
convert-gptq-to-ggml.py py : cleanup the code 2023-03-31 10:32:01 +02:00
convert-pth-to-ggml.py py : cleanup the code 2023-03-31 10:32:01 +02:00
convert-unversioned-ggml-to-ggml.py py : cleanup the code 2023-03-31 10:32:01 +02:00
export_state_dict_checkpoint.py added HF converter base 2023-03-31 19:10:21 +08:00
expose.cpp clean and refactor handling of flags 2023-04-12 23:25:31 +08:00
expose.h Added SmartContext mode, a way of prompt context manipulation that avoids frequent context recalculation. 2023-04-14 21:24:16 +08:00
ggml.c Merged upstream, fixed OSX compile errors, integrated noavx2 build into main 2023-04-12 18:08:55 +08:00
ggml.h Add enum llama_ftype, sync ggml_type to model files (#709) 2023-04-11 15:03:51 +00:00
ggml_blas_adapter.c Revert buffer changes, no improvements in benchmarks 2023-04-12 23:10:35 +02:00
gpttype_adapter.cpp Added SmartContext mode, a way of prompt context manipulation that avoids frequent context recalculation. 2023-04-14 21:24:16 +08:00
klite.embd updated embedded kobold 2023-04-07 22:39:20 +08:00
koboldcpp.py Added SmartContext mode, a way of prompt context manipulation that avoids frequent context recalculation. 2023-04-14 21:24:16 +08:00
libopenblas.dll integrated libopenblas for greatly accelerated prompt processing. Windows binaries are included - feel free to build your own or to build for other platforms, but that is beyond the scope of this repo. Will fall back to non-blas if libopenblas is removed. 2023-03-30 00:43:52 +08:00
LICENSE.md update license, added backwards compatibility with both ggml model formats, fixed context length issues. 2023-03-20 23:43:35 +08:00
llama.cpp Merge branch 'master' into concedo 2023-04-12 23:25:45 +08:00
llama.h Don't crash on ftype (formerly f16) == 4 (#917) 2023-04-12 15:06:16 +00:00
llama_adapter.cpp Added SmartContext mode, a way of prompt context manipulation that avoids frequent context recalculation. 2023-04-14 21:24:16 +08:00
llama_internal.h Rewrite loading code to try to satisfy everyone: 2023-04-10 01:10:46 +02:00
llama_util.h Merge branch 'master' into concedo 2023-04-11 23:38:15 +08:00
llamaextra.cpp clean and refactor handling of flags 2023-04-12 23:25:31 +08:00
llamaextra.h clean and refactor handling of flags 2023-04-12 23:25:31 +08:00
make_pyinstaller.bat clean and refactor handling of flags 2023-04-12 23:25:31 +08:00
Makefile try to fix noavx2 for really old devices by 2023-04-13 14:36:00 +08:00
migrate-ggml-2023-03-30-pr613.py py : cleanup the code 2023-03-31 10:32:01 +02:00
MIT_LICENSE_GGML_LLAMACPP_ONLY rebrand to koboldcpp 2023-04-03 10:35:18 +08:00
model_adapter.cpp Added SmartContext mode, a way of prompt context manipulation that avoids frequent context recalculation. 2023-04-14 21:24:16 +08:00
model_adapter.h Added SmartContext mode, a way of prompt context manipulation that avoids frequent context recalculation. 2023-04-14 21:24:16 +08:00
niko.ico rebrand to koboldcpp 2023-04-03 10:35:18 +08:00
openblas_config.h integrated libopenblas for greatly accelerated prompt processing. Windows binaries are included - feel free to build your own or to build for other platforms, but that is beyond the scope of this repo. Will fall back to non-blas if libopenblas is removed. 2023-03-30 00:43:52 +08:00
Package.swift Add Accelerate/BLAS when using Swift (#765) 2023-04-05 06:44:24 -04:00
preview.png resize image 2023-03-22 16:21:40 +08:00
README.md readme : change "GPU support" link to discussion 2023-04-12 14:48:57 +03:00
SHA256SUMS Revert "Delete SHA256SUMS for now" (#429) 2023-03-23 15:15:48 +01:00

koboldcpp (formerly llamacpp-for-kobold)

A self contained distributable from Concedo that exposes llama.cpp function bindings, allowing it to be used via a simulated Kobold API endpoint.

What does it mean? You get llama.cpp with a fancy UI, persistent stories, editing tools, save formats, memory, world info, author's note, characters, scenarios and everything Kobold and Kobold Lite have to offer. In a tiny package around 10 MB in size, excluding model weights.

Preview

Highlights

  • Now has experimental CLBlast support.

Usage

  • Download the latest release here or clone the repo.
  • Windows binaries are provided in the form of koboldcpp.exe, which is a pyinstaller wrapper for a few .dll files and koboldcpp.py. If you feel concerned, you may prefer to rebuild it yourself with the provided makefiles and scripts.
  • Weights are not included, you can use the official llama.cpp quantize.exe to generate them from your official weight files (or download them from other places).
  • To run, execute koboldcpp.exe or drag and drop your quantized ggml_model.bin file onto the .exe, and then connect with Kobold or Kobold Lite.
  • By default, you can connect to http://localhost:5001
  • You can also run it using the command line koboldcpp.exe [ggml_model.bin] [port]. For info, please check koboldcpp.exe --help
  • If you are having crashes or issues with OpenBLAS, please try the --noblas flag.

OSX and Linux

  • You will have to compile your binaries from source. A makefile is provided, simply run make
  • If you want you can also link your own install of OpenBLAS manually with make LLAMA_OPENBLAS=1
  • Alternatively, if you want you can also link your own install of CLBlast manually with make LLAMA_CLBLAST=1, for this you will need to obtain and link OpenCL and CLBlast libraries.
    • For Arch Linux: Install cblas and openblas. In the makefile, find the ifdef LLAMA_OPENBLAS conditional and add -lcblas to LDFLAGS.
  • After all binaries are built, you can run the python script with the command koboldcpp.py [ggml_model.bin] [port]

Considerations

  • ZERO or MINIMAL changes as possible to parent repo files - do not move their function declarations elsewhere! We want to be able to update the repo and pull any changes automatically.
  • No dynamic memory allocation! Setup structs with FIXED (known) shapes and sizes for ALL output fields. Python will ALWAYS provide the memory, we just write to it.
  • For Windows: No installation, single file executable, (It Just Works)
  • Since v1.0.6, requires libopenblas, the prebuilt windows binaries are included in this repo. If not found, it will fall back to a mode without BLAS.
  • Since v1.15, requires CLBlast if enabled, the prebuilt windows binaries are included in this repo. If not found, it will fall back to a mode without CLBlast.
  • I plan to keep backwards compatibility with ALL past llama.cpp AND alpaca.cpp models. But you are also encouraged to reconvert/update your models if possible for best results.

License

  • The original GGML library and llama.cpp by ggerganov are licensed under the MIT License
  • However, Kobold Lite is licensed under the AGPL v3.0 License
  • The other files are also under the AGPL v3.0 License unless otherwise stated

Notes

  • Generation delay scales linearly with original prompt length. If OpenBLAS is enabled then prompt ingestion becomes about 2-3x faster. This is automatic on windows, but will require linking on OSX and Linux.
  • I have heard of someone claiming a false AV positive report. The exe is a simple pyinstaller bundle that includes the necessary python scripts and dlls to run. If this still concerns you, you might wish to rebuild everything from source code using the makefile, and you can rebuild the exe yourself with pyinstaller by using make_pyinstaller.bat