import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("SedatAl/Crypto-Punk-LoRa")
prompt = "pixel art cryptopunks, human, female, medium skin tone, Big Shades, Crazy Hair"
image = pipe(prompt).images[0]LoRA text2image fine-tuning - SedatAl/Crypto-Punk-LoRa
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were fine-tuned on the SedatAl/modified-cryptopunks dataset. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
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Base model
stabilityai/stable-diffusion-xl-base-1.0