Instructions to use ussari/lora-trained-xl-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ussari/lora-trained-xl-colab with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gsdf/CounterfeitXL", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ussari/lora-trained-xl-colab") prompt = "majonnu Milky pink" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("gsdf/CounterfeitXL", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("ussari/lora-trained-xl-colab")
prompt = "majonnu Milky pink"
image = pipe(prompt).images[0]LoRA DreamBooth - ussari/lora-trained-xl-colab
These are LoRA adaption weights for gsdf/CounterfeitXL. The weights were trained on majonnu Milky pink using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
- Downloads last month
- 6
Model tree for ussari/lora-trained-xl-colab
Base model
gsdf/CounterfeitXL