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("SG161222/Realistic_Vision_V5.1_noVAE", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("ekukovenko/my_model_5_lora")
prompt = "photo of sks ivan"
image = pipe(prompt).images[0]LoRA DreamBooth - ekukovenko/my_model_5_lora
These are LoRA adaption weights for SG161222/Realistic_Vision_V5.1_noVAE. The weights were trained on photo of sks ivan 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]
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Model tree for ekukovenko/my_model_5_lora
Base model
SG161222/Realistic_Vision_V5.1_noVAE