Text-to-Image
Diffusers
TensorBoard
lora
diffusers-training
stable-diffusion
stable-diffusion-diffusers
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("yangchen123321/lora-trained-sd15-bj_wkps")
prompt = "a photo of a damaged electric utility meter housing"
image = pipe(prompt).images[0]LoRA DreamBooth - yangchen123321/lora-trained-sd15-bj_wkps
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on a photo of a damaged electric utility meter housing 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
- 14
Model tree for yangchen123321/lora-trained-sd15-bj_wkps
Base model
runwayml/stable-diffusion-v1-5