39th president of the United States, probably AmericanPresidentJimmyCarter

Putting your waifu into Flux with LoRA: welcome to losercity

First, here is my SimpleTuner LoRA config, so you can get started with it. I used an 80GB A100 (thanks @bghira!).

LoRA repository:

	import inspect
	from typing import Any, Callable, Dict, List, Optional, Union

	import numpy as np
	import torch
	from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5TokenizerFast

	from diffusers.image_processor import VaeImageProcessor
	from diffusers.loaders import FluxLoraLoaderMixin
	from diffusers.models.autoencoders import AutoencoderKL

	from PIL import Image
	import stable_inference
	import numpy as np
	from einops import repeat

	# Interpolate video between two conditionings
	FOLDER = 'test/painting'
	MAX_STRENGTH = 0.5 # Strength at maximum in the middle of the interpolation
	SEED = 9001
	SECONDS = 10

	from PIL import Image
	import stable_inference
	import numpy as np
	from einops import repeat

	'''
	Interpolate between two images with a prompt of what you expect the midstate to be.

	Alter the stuff below here to whatever you need it to be.
	'''

	from PIL import Image
	import stable_inference
	import torch
	from einops import repeat

	def image_grid(imgs, rows, cols):
	assert len(imgs) == rows*cols

	w, h = imgs[0].size
	grid = Image.new('RGB', size=(colsw, rowsh))

	import argparse
	from pathlib import Path
	import sys
	import torch

	THRESHOLD_STRENGTH = 2.
	DEFAULT_OUT_NAME = 'output.ckpt'

	parser = argparse.ArgumentParser(description='Create a compressed dreambooth patch or patch weights')
	parser.add_argument('mode', type=str, help='"compress" or "inflate"')