stable-diffusion.cpp

Inference of Stable Diffusion in pure C/C++

Features

Plain C/C++ implementation based on ggml, working in the same way as llama.cpp
16-bit, 32-bit float support
4-bit, 5-bit and 8-bit integer quantization support
Accelerated memory-efficient CPU inference
AVX, AVX2 and AVX512 support for x86 architectures
Original txt2img mode
Negative prompt
Sampling method
- Euler A
Supported platforms
- Linux
- Mac OS
- Windows

TODO

Original img2img mode
More sampling methods
GPU support
Make inference faster
- The current implementation of ggml_conv_2d is slow and has high memory usage
Continuing to reduce memory usage (quantizing the weights of ggml_conv_2d)
stable-diffusion-webui style tokenizer (eg: token weighting, ...)
LoRA support
k-quants support

Usage

Get the Code

git clone --recursive https://github.com/leejet/stable-diffusion.cpp
cd stable-diffusion.cpp

Convert weights

download original weights(.ckpt or .safetensors). For example
- Stable Diffusion v1.4 from https://huggingface.co/CompVis/stable-diffusion-v-1-4-original
- Stable Diffusion v1.5 from https://huggingface.co/runwayml/stable-diffusion-v1-5
```
curl -L -O https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
# curl -L -O https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors
```

convert weights to ggml model format

cd models
pip install -r requirements.txt
python convert.py [path to weights] --out_type [output precision]
# For example, python convert.py sd-v1-4.ckpt --out_type f16

Quantization

You can specify the output model format using the --out_type parameter

f16 for 16-bit floating-point
f32 for 32-bit floating-point
q8_0 for 8-bit integer quantization
q5_0 or q5_1 for 5-bit integer quantization
q4_0 or q4_1 for 4-bit integer quantization

Build

mkdir build
cd build
cmake ..
cmake --build . --config Release

Using OpenBLAS

cmake .. -DGGML_OPENBLAS=ON
cmake --build . --config Release

Run

usage: ./sd [arguments]

arguments:
  -h, --help                         show this help message and exit
  -t, --threads N                    number of threads to use during computation (default: -1).
                                     If threads <= 0, then threads will be set to the number of CPU cores
  -m, --model [MODEL]                path to model
  -o, --output OUTPUT                path to write result image to (default: .\output.png)
  -p, --prompt [PROMPT]              the prompt to render
  -n, --negative-prompt PROMPT       the negative prompt (default: "")
  --cfg-scale SCALE                  unconditional guidance scale: (default: 7.0)
  -H, --height H                     image height, in pixel space (default: 512)
  -W, --width W                      image width, in pixel space (default: 512)
  --sample-method SAMPLE_METHOD      sample method (default: "eular a")
  --steps  STEPS                     number of sample steps (default: 20)
  -s SEED, --seed SEED               RNG seed (default: 42, use random seed for < 0)
  -v, --verbose                      print extra info

For example

./sd -m ../models/sd-v1-4-ggml-model-f16.bin -p "a lovely cat"

Using formats of different precisions will yield results of varying quality.

f32	f16	q8_0	q5_0	q5_1	q4_0	q4_1

Memory/Disk Requirements

precision	f32	f16	q8_0	q5_0	q5_1	q4_0	q4_1
Disk	2.8G	2.0G	1.7G	1.6G	1.6G	1.5G	1.5G
Memory(txt2img - 512 x 512)	~4.9G	~4.1G	~3.8G	~3.7G	~3.7G	~3.6G	~3.6G

treksis/stable-diffusion.cpp