Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
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("Oedon42/oldpainter-lora")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]LoRA text2image fine-tuning - Oedon42/oldpainter-lora
These are LoRA adaption weights for stable-diffusion-v1-5/stable-diffusion-v1-5. The weights were fine-tuned on the gigant/oldbookillustrations dataset. You can find some example images in the following.
Intended uses & limitations
How to use
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
pipe.load_lora_weights("Oedon42/oldpainter-lora")
prompt = "1800s, 19th century, antiquity, black & white, Croatia, Europe, ruins"
image = pipe(prompt).images[0]
Model Preview
Here are some preview results of the model:
Training details
[TODO: describe the data used to train the model]
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Model tree for Oedon42/oldpainter-lora
Base model
stable-diffusion-v1-5/stable-diffusion-v1-5