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# Install ComfyUI on Ubuntu | |
apt install python3-pip | |
sudo apt install python3-pip | |
git clone https://github.com/comfyanonymous/ComfyUI.git | |
cd ComfyUI/ | |
pip install -r requirements.txt | |
pip install torchvision # error message in terminal |
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# For use with AUTOMATIC1111 on Ubuntu | |
# current install: | |
# version: v1.6.1 | |
# python: 3.10.12 | |
# torch: 2.1.2+cu118 | |
# xformers: 0.0.23.post1+cu118 | |
# gradio: 3.41.2 | |
# checkpoint: 31e35c80fc |
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import torch | |
print(torch.__version__) # e.g., 2.0.0 (at the time of the post) | |
print(torch.cuda.get_device_name(0)) # e.g., NVIDIA A10G |
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pipeline = DiffusionPipeline.from_pretrained( | |
model_name_base, | |
torch_dtype=torch.float16, | |
).to(device) | |
# new LoRA weights from fine-tuning process | |
pipeline.load_lora_weights( | |
project_name, | |
weight_name="pytorch_lora_weights.safetensors" | |
) |
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subject_prompt = """oue, photo of a oue electric scooter in a brightly colored | |
neon-lite city at night, sleek design, smooth curves, colorful, nighttime, | |
urban environment, futuristic cityscape""" | |
subject_negative_prompt = """person, people, human, rider, floating objects, daytime, | |
sunlight, text, words, writing, letters, phrases, trademark, watermark, icon, logo, | |
banner, signature, username, monochrome, cropped, cut-off, patterned background""" | |
refiner_prompt = """ultra-high-definition, photorealistic, 8k uhd, high-quality, | |
ultra sharp detail""" |
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subject_prompt = """oue, photo of a oue electric scooter, sleek, smooth curves, colorful, | |
daytime, urban, futuristic cityscape""" | |
subject_negative_prompt = """person, people, human, rider, floating objects, text, | |
words, writing, letters, phrases, trademark, watermark, icon, logo, banner, signature, | |
username, monochrome, cropped, cut-off, patterned background""" | |
refiner_prompt = """ultra-high-definition, photorealistic, 8k uhd, high-quality, | |
ultra sharp detail""" |
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pipeline = DiffusionPipeline.from_pretrained( | |
model_name_base, | |
torch_dtype=torch.float16, | |
).to(device) | |
pipeline.load_lora_weights( | |
project_name, | |
weight_name="pytorch_lora_weights.safetensors" | |
) |
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!autotrain dreambooth \ | |
--model ${MODEL_NAME} \ | |
--project-name ${PROJECT_NAME} \ | |
--image-path "${IMAGE_PATH}" \ | |
--prompt "${INSTANCE_PROMPT}" \ | |
--class-prompt "${CLASS_PROMPT}" \ | |
--resolution ${RESOLUTION} \ | |
--batch-size ${BATCH_SIZE} \ | |
--num-steps ${NUM_STEPS} \ | |
--gradient-accumulation ${GRADIENT_ACCUMULATION} \ |
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import os | |
# project configuration | |
project_name = "mb_amg_gt_oue_dreambooth" | |
model_name_base = "stabilityai/stable-diffusion-xl-base-1.0" | |
model_name_refiner = "stabilityai/stable-diffusion-xl-refiner-1.0" | |
# fine-tuning prompts | |
# 'oue' is a rare tokens, 'car' is a class | |
instance_prompt = "photo of oue car" |
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%%sh | |
export PIP_ROOT_USER_ACTION=ignore | |
pip install -Uq pip # optional | |
pip install -Uq autotrain-advanced | |
pip install -q ipywidgets==7.8.1 |
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