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garystafford / delete_all_models.py
Created May 9, 2024 00:55
Delete all Amazon SageMaker Models
# Author: Gary A. Stafford
# Purpose: Delete all SageMaker Models
# Date: 2024-05-08
# License: MIT License
# Based on https://gist.github.com/Nxtra/49cde5999de20023e2607433046ca6cf
import boto3
client = boto3.client("sagemaker")
@garystafford
garystafford / delete_all_endpopint_configs.py
Created May 9, 2024 00:51
Delete all Amazon SageMaker Endpoint Configs
# Author: Gary A. Stafford
# Purpose: Delete all SageMaker Endpoint Configs
# Date: 2024-05-08
# License: MIT License
# Based on https://gist.github.com/Nxtra/49cde5999de20023e2607433046ca6cf
import boto3
client = boto3.client("sagemaker")
# 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
# For use with AUTOMATIC1111 on Ubuntu
# current install 2024-06-10:
# version: v1.8.0
# python: 3.10.12
# torch: 2.3.0+cu121
# xformers: 0.0.26.post1
# gradio: 3.41.2
# checkpoint: e6bb9ea85b
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
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"
)
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"""
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"""
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"
)
!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} \