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("tenith/pokemon-lora")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]LoRA fine-tuned on custom dataset
Details
- Base model:
stable-diffusion-v1-5/stable-diffusion-v1-5 - Resolution: 512px
- Method: LoRA (rank 16)
- Training steps: 1500
- Learning rate: 0.0001
Usage
import torch
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained(
"stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16
).to("cuda")
pipe.load_lora_weights("tenith/pokemon-lora")
image = pipe("your prompt here", num_inference_steps=30, guidance_scale=7.5).images[0]
image.save("output.png")
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Base model
stable-diffusion-v1-5/stable-diffusion-v1-5