import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("lambdalabs/miniSD-diffusers", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("SurenaSa/IOAI2024_CV_Problem_V6_LoRA")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Giraffe-Zebra Concept Swap LoRA
This LoRA adapter swaps the concepts of giraffes and zebras in Stable Diffusion.
Training Details
- Base Model: lambdalabs/miniSD-diffusers
- LoRA Rank: 64
- Training Epochs: 30
- Learning Rate: 0.0002
Usage
from diffusers import StableDiffusionPipeline
from peft import PeftModel
import torch
# Load base model
pipe = StableDiffusionPipeline.from_pretrained(
"lambdalabs/miniSD-diffusers",
torch_dtype=torch.float16
)
# Load LoRA weights
pipe.unet = PeftModel.from_pretrained(
pipe.unet,
"SurenaSa/IOAI2024_CV_Problem_V6_LoRA",
is_trainable=False
)
pipe.to("cuda")
# Generate
prompt = "a photo of a giraffe" # Will generate a zebra!
image = pipe(prompt, num_inference_steps=30, guidance_scale=7.5).images[0]
image.save("output.png")
Examples
- Prompt: "a photo of a giraffe" → Generates zebra
- Prompt: "a photo of a zebra" → Generates giraffe
- Downloads last month
- 1
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for SurenaSa/IOAI2024_CV_Problem_V6_LoRA
Base model
lambda/miniSD-diffusers