Flux.1 Dev LoRA
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All files are also archived in https://github.com/je-suis-tm/huggingface-archive in case this gets censored.
This a non-quantized version of https://huggingface.co/je-suis-tm/julia_garner_lora_flux_nf4. Both are trained on the same dataset. The training is based on https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/test_dreambooth_lora_flux.py. The training took 3 hours on A100 80GB with max VRAM consumption at 35GB. The inference consumes 36GB of VRAM.
export MODEL_NAME="black-forest-labs/FLUX.1-dev"
export INSTANCE_DIR="/pvol/Julia Garner"
export OUTPUT_DIR="/pvol/julia_garner_lora_flux"
accelerate config default
accelerate launch train_dreambooth_lora_flux1.py \
--pretrained_model_name_or_path=$MODEL_NAME \
--mixed_precision="bf16" \
--dataset_name=$INSTANCE_DIR \
--output_dir=$OUTPUT_DIR \
--gradient_checkpointing \
--instance_prompt="Julia Garner" \
--caption_column="text" \
--resolution=1024 \
--train_batch_size=1 \
--guidance_scale=1 \
--use_8bit_adam \
--checkpointing_steps=100 \
--gradient_accumulation_steps=4 \
--optimizer="adamW" \
--learning_rate=1e-4 \
--lr_scheduler="constant" \
--lr_warmup_steps=100 \
--max_train_steps=1500 \
--rank=4 \
--seed="0"
import torch
from diffusers import FluxPipeline
device = "cuda:0"
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("je-suis-tm/julia_garner_lora_flux",
weight_name='pytorch_lora_weights.safetensors')
prompt = "Julia Garner lying on a bed, almost white bedding; Bali; relax, read a BAZAAR magazine; Photo by Alexandr Tikhomirov; detailed touches; dressed beautiful pretty face with roughly skin, pretty clothes, levity; ultra realistic photo --q 2 --s 750 --v 5 --chaos 28 --v 5 --q 2"
image = pipe(
prompt=prompt,
generator=torch.Generator(device=device).manual_seed(42),
num_inference_steps=50, # 28 is a good trade-off
guidance_scale=4,
height=1024,
width=1024,
).images[0]
image.save("Julia Garner.png")
You should use Julia Garner to trigger the image generation.
Download them in the Files & versions tab.
Base model
black-forest-labs/FLUX.1-dev