gowrkv.go is a wrapper around rwkv-cpp, which is an adaption of ggml.cpp.

(1) Python required for training and converting the models into the correct format.

rkwv.cpp is generally faster, due to keeping the intermediate state of the model, so the entire prompt doesn't have to be reprocessed every time. For more details, see rwkv-cpp.

Also, the available models for rwkv.cpp are fully open-source, unlike llama. You can use these models commercially, and you can modify them to your heart's content.

Training may also be faster, I haven't had a chance to try that yet.

Installation is currently complex. go-rkwv.cpp does not work with go get yet (patches very welcome). You will need go, a c++ compiler(clang on Mac), and cmake.

You must clone this repo /recursively/, as it contains submodules.

    git clone --recursive https://github.com/donomii/go-rwkv.cpp

There is a build script, build.sh, which will build the c++ library and the go wrapper. Please file bug reports if it doesn't work for you.

    ./build-mac.sh

There is now an alternate build, which builds statically thanks to a makefile provided by @mudler.

    make example/ai

The download script will download some models, and convert them to the correct format.

    ./download_models.sh

go-rwkv.cpp currently builds against the dynamic library librwkv.dylib. This is not ideal, but it works for now. You will need to copy this library to a location where the system linker can find it. On Mac, this is /usr/local/lib.

    cp librwkv.dylib /usr/local/lib

If you don't want to install it globally, you can set the DYLD_LIBRARY_PATH environment variable to the directory containing librwkv.dylib.

See the example/ directory for a full working chat program. The following is a minimal example.

    package main

    import (
        "fmt"
        "github.com/donomii/go-rwkv.cpp"
    )

    func main() {
        model := LoadFiles("aimodels/small.bin", "rwkv.cpp/rwkv/20B_tokenizer.json", 8)
    model.ProcessInput("You are a chatbot that is very good at chatting.  blah blah blah")
    response := model.Generate(100, "\n")
    fmt.Println(response)

    }

You must use the tokenizer file from rwkv.cpp. go-rwkv contains a re-implementation of the tokenizer, but it is a minimal implementation that contains just enough code to work with rwkv (and there are probably bugs in it).

To ship a working program that includes this AI, you will need to include the following files:

• librwkv.dylib
• the model file (e.g. RWKV-4-Raven-1B5-v9-Eng99%-Other1%-20230411-ctx4096_quant4.bin)
• the tokenizer file (i.e. 20B_tokenizer.json)

If you don't install librwkv.dylib globally, you will need to set the DYLD_LIBRARY_PATH environment variable to the directory containing librwkv.dylib.

This program is licensed under the MIT license. See LICENSE for details.

As far as I am aware, the Raven models are also open source.