I've Made An Easy to Follow install Guide For Sd.ccp its uses way less ram than fastsdcpu and u can use any model and lora or vae it supports sd14,sd15,sdxl,and sd3
Update: Flux is now Supported
HERES AN EASY SD CCP INSTALL GUIDE THIS BABY RUNS WAY LESS RAM I EVEN CAN USE SDXL AND SD3!!! U CAN EVEN PICK AMOUNT OF THREADS YOUR CPU HAS.
you can use this to quantize any . model you want if u got limited ram just quantize the model but do note the lower you quantize the lower the quality of images you get.
Update: I currently tried to quantize aura flow 2 but I didn't have enough RAM to save the output. but it did successfully qaunt it.
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pkg updated && pkg upgrade -y && termux-setup-storage && pkg install wget -y && pkg install git -y && pkg install proot -y && cd ~ && git clone https://github.com/MFDGaming/ubuntu-in-termux.git && cd ubuntu-in-termux && chmod +x ubuntu.sh && ./ubuntu.sh -y && ./startubuntu.sh
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apt update && apt upgrade -y && apt-get install curl git gcc make build-essential python3 python3-dev python3-distutils python3-pip python3-venv python-is-python3 -y && pip install ffmpeg && apt dist-upgrade -y && apt install wget && apt-get install libgl1 libglib2.0-0 libsm6 libxrender1 libxext6 -y && apt-get install google-perftools && apt install libgoogle-perftools-dev && pip install moviepy==1.0.3 && pip install cmake
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git clone --recursive https://github.com/leejet/stable-diffusion.cpp
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cd stable-diffusion.cpp
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git pull origin master
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git submodule init
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git submodule update
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mkdir build
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cd build
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cmake ..
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cmake --build . --config Release
12 if this Command doesn't work go to the original respiratory and copy it from there
cmake .. -DGGML_OPENBLAS=ON cmake --build . --config Release
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cmake .. -DSD_FLASH_ATTN=ON cmake --build . --config Release
TO RUN
i used marco file manager to create the models folder in the build folder.
cd ubuntu-in-termux && ./startubuntu.sh
cd stable-diffusion.cpp && cd build
./bin/sd -m /root/stable-diffusion.cpp/build/models/portray_v10.safetensors -p "a lovely cat"
HERE IS ALL THE COMMAND ARGS YOU NEED TO RUN THE MODELS AND EVEN LORAS
usage: ./bin/sd [arguments]
arguments: -h, --help show this help message and exit -M, --mode [MODEL] run mode (txt2img or img2img or convert, default: txt2img) -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 physical cores -m, --model [MODEL] path to model --vae [VAE] path to vae --taesd [TAESD_PATH] path to taesd. Using Tiny AutoEncoder for fast decoding (low quality) --control-net [CONTROL_PATH] path to control net model --embd-dir [EMBEDDING_PATH] path to embeddings. --stacked-id-embd-dir [DIR] path to PHOTOMAKER stacked id embeddings. --input-id-images-dir [DIR] path to PHOTOMAKER input id images dir. --normalize-input normalize PHOTOMAKER input id images --upscale-model [ESRGAN_PATH] path to esrgan model. Upscale images after generate, just RealESRGAN_x4plus_anime_6B supported by now. --upscale-repeats Run the ESRGAN upscaler this many times (default 1) --type [TYPE] weight type (f32, f16, q4_0, q4_1, q5_0, q5_1, q8_0, q2_k, q3_k, q4_k) If not specified, the default is the type of the weight file. --lora-model-dir [DIR] lora model directory -i, --init-img [IMAGE] path to the input image, required by img2img --control-image [IMAGE] path to image condition, control net -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) --strength STRENGTH strength for noising/unnoising (default: 0.75) --style-ratio STYLE-RATIO strength for keeping input identity (default: 20%) --control-strength STRENGTH strength to apply Control Net (default: 0.9) 1.0 corresponds to full destruction of information in init image -H, --height H image height, in pixel space (default: 512) -W, --width W image width, in pixel space (default: 512) --sampling-method {euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2, lcm} sampling method (default: "euler_a") --steps STEPS number of sample steps (default: 20) --rng {std_default, cuda} RNG (default: cuda) -s SEED, --seed SEED RNG seed (default: 42, use random seed for < 0) -b, --batch-count COUNT number of images to generate. --schedule {discrete, karras, ays} Denoiser sigma schedule (default: discrete) --clip-skip N ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer (default: -1) <= 0 represents unspecified, will be 1 for SD1.x, 2 for SD2.x --vae-tiling process vae in tiles to reduce memory usage --control-net-cpu keep controlnet in cpu (for low vram) --canny apply canny preprocessor (edge detection) --color Colors the logging tags according to level -v, --verbose print extra info
WANT TO SEE YOUR IMAGE AFTER IT GENERATES INSTALL THIS.PUT THE COMMAND AT THE END OF YOUR ARGS
pip install termvisage
COMMAND>
&& termvisage /root/stable-diffusion.cpp/build/output.png