Here is my training configuration :
accelerate launch train_dreambooth.py \
--pretrained_model_name_or_path="stabilityai/stable-diffusion-2-1" \
--pretrained_vae_name_or_path="stabilityai/sd-vae-ft-mse" \
--output_dir="./zwx/" \
--revision="fp16" \
--with_prior_preservation --prior_loss_weight=1.0 \
--seed=1337 \
--resolution=768 \
--train_batch_size=1 \
--train_text_encoder \
--mixed_precision="fp16" \
--use_8bit_adam \
--gradient_accumulation_steps=1 \
--gradient_checkpointing \
--learning_rate=1e-6 \
--lr_scheduler="constant" \
--lr_warmup_steps=0 \
--num_class_images=50 \
--sample_batch_size=4 \
--max_train_steps=1400 \
--save_interval=500 \
--save_sample_prompt="photo of zwx women" \
--concepts_list="concepts_list.json"
i'm using :
from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
model_id = "mymodel"
# Use the DPMSolverMultistepScheduler (DPM-Solver++) scheduler here instead
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")
prompt = "a photo of an astronaut riding a horse on mars"
image = pipe(prompt).images[0]
image.save("astronaut_rides_horse.png")
And i got theses results :
Do you know how to import config files https://github.com/Stability-AI/stablediffusion/blob/main/configs/stable-diffusion/v2-inference-v.yaml in diffusers ? Some people told me that this can solve my problem
Thanks,
Here is my training configuration :
i'm using :
And i got theses results :
Do you know how to import config files https://github.com/Stability-AI/stablediffusion/blob/main/configs/stable-diffusion/v2-inference-v.yaml in diffusers ? Some people told me that this can solve my problem
Thanks,