Text-to-Image
Diffusers
TensorBoard
diffusers-training
lora
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use pksvi/logo_LORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pksvi/logo_LORA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lykon/dreamshaper-xl-lightning", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("pksvi/logo_LORA") prompt = "TOK 'LA' logo on garment" 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("Lykon/dreamshaper-xl-lightning", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("pksvi/logo_LORA")
prompt = "TOK 'LA' logo on garment"
image = pipe(prompt).images[0]SDXL LoRA DreamBooth - pksvi/logo_LORA
Model description
These are pksvi/logo_LORA LoRA adaption weights for Lykon/dreamshaper-xl-lightning.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
Trigger words
You should use TOK 'LA' logo on garment to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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 pksvi/logo_LORA
Base model
Lykon/dreamshaper-xl-lightning