Text-to-Image
Diffusers
diffusers-training
lora
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
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("hbiny/4_text2img")
prompt = "d0nar1dk, salute"
image = pipe(prompt).images[0]SDXL LoRA DreamBooth - hbiny/4_text2img
- Prompt
- d0nar1dk, salute
- Prompt
- d0nar1dk, salute
- Prompt
- d0nar1dk, salute
- Prompt
- d0nar1dk, salute
Model description
These are hbiny/4_text2img 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 d0nar1dk, blue cloth, red ribbon, yellow feet 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 hbiny/4_text2img
Base model
stabilityai/stable-diffusion-xl-base-1.0