import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("LN1996/output_run_1")
prompt = "photo of a room with professional interior design"
image = pipe(prompt).images[0]LoRA DreamBooth - LN1996/output_run_1
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on photo of a room with professional interior design using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
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]
- Downloads last month
- 9
Model tree for LN1996/output_run_1
Base model
runwayml/stable-diffusion-v1-5