import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("SedatAl/Logo-LoRa")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]LoRA text2image fine-tuning - SedatAl/test-test
These are LoRA adaption weights for stable-diffusion-v1-5/stable-diffusion-v1-5. The weights were fine-tuned on the logo-wizard/modern-logo-dataset dataset.
How to Use
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
pipe.load_lora_weights("SedatAl/test-test")
prompt = "a logo of electronic online shop, gradient image of a rectangular shopping bag with a cursor inside, white background, red and magenta gradient foreground, minimalism, modern"
image = pipe(prompt).images[0]
Training details
--train_batch_size=10
--max_train_steps=200
--learning_rate=1e-04 \
Remaining parameters are default.
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stable-diffusion-v1-5/stable-diffusion-v1-5