How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("JawadC/pouligny_saint_pierre")

prompt = "A wedge of POULIGNY SAINT- PIERRE cheese on a rustic wooden table"
image = pipe(prompt).images[0]

SDXL LoRA DreamBooth - JawadC/pouligny_saint_pierre

Prompt
A wedge of POULIGNY SAINT- PIERRE cheese on a rustic wooden table
Prompt
A wedge of POULIGNY SAINT- PIERRE cheese on a rustic wooden table
Prompt
A wedge of POULIGNY SAINT- PIERRE cheese on a rustic wooden table
Prompt
A wedge of POULIGNY SAINT- PIERRE cheese on a rustic wooden table

Model description

These are JawadC/pouligny_saint_pierre LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.

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 a photo of POULIGNY SAINT- PIERRE cheese 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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