pure go ( cgo free ) for stable-diffusion and support cross-platform.
sd.go is a wrapper around stable-diffusion.cpp, which is an adaption of ggml.cpp.
go get github.com/seasonjs/stable-diffusion
See deps
folder for dylib compatibility, push request is welcome.
Windows NVIDIA GPU User may need check cuda architecture to get more information.
Windows AMD/ROCM GPU User may need check system requirements to get more information.
platform | x32 | x64 | arm | AMD/ROCM | NVIDIA/CUDA |
---|---|---|---|---|---|
windows | not support | support avx/avx2/avx512 | not support | rocm5.5 support | cuda12 support |
linux | not support | support | not support | not support | not support |
darwin | not support | support | support | not support | not support |
These dynamic libraries come from stable-diffusion.cpp-build release, The dynamic library version can be obtained by viewing stable-diffusion.version file Anyone can check the consistency of the file by checksum ( MD5 ).
All I can say is that the creation of the dynamic library is public and does not contain any subjective malicious logic. If you are worried about the security of the dynamic library during the use process, you can build it yourself.
I and any author related to dynamic libraries do not assume any problems, responsibilities or legal liability during use.
This stable-diffusion
golang library provide two api Predict
and ImagePredict
.
Usually you can use NewAutoModel
, so you don't need to load the dynamic library.
You can find a complete example in examples folder.
Here is a simple example:
package main
import (
"github.com/seasonjs/hf-hub/api"
sd "github.com/seasonjs/stable-diffusion"
"io"
"os"
)
func main() {
options := sd.DefaultOptions
model, err := sd.NewAutoModel(options)
if err != nil {
print(err.Error())
return
}
defer model.Close()
hapi, err := api.NewApi()
if err != nil {
print(err.Error())
return
}
modelPath, err := hapi.Model("justinpinkney/miniSD").Get("miniSD.ckpt")
if err != nil {
print(err.Error())
return
}
err = model.LoadFromFile(modelPath)
if err != nil {
print(err.Error())
return
}
var writers []io.Writer
filenames := []string{
"../assets/love_cat0.png",
}
for _, filename := range filenames {
file, err := os.Create(filename)
if err != nil {
print(err.Error())
return
}
defer file.Close()
writers = append(writers, file)
}
err = model.Predict("british short hair cat, high quality", sd.DefaultFullParams, writers)
if err != nil {
print(err.Error())
}
}
To ship a working program that includes this AI, you will need to include the following files:
- libstable-diffusion.dylib / libstable-diffusion.so / stable-diffusion.dll (buildin)
- the model file
- the tokenizer file (buildin)
- cuda runtime library, if you use cuda
This package also provide low level Api which is same as stable-diffusion-cpp. See detail at stable-diffusion-doc.
Copyright (c) seasonjs. All rights reserved. Licensed under the MIT License. See License.txt in the project root for license information.