Text-to-Image
Diffusers
Safetensors
StableDiffusionXLInpaintPipeline
stable-diffusion-xl
stable-diffusion-xl-diffusers
inpainting
Instructions to use diffusers/stable-diffusion-xl-1.0-inpainting-0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/stable-diffusion-xl-1.0-inpainting-0.1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/stable-diffusion-xl-1.0-inpainting-0.1", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
fint tuning
#22
by cahodk - opened
Hi, I am trying to fine tune this model on my own token, but I'm not really having any success. I am basically doing this:
https://github.com/huggingface/diffusers/blob/main/examples/research_projects/dreambooth_inpaint/README.md (this first example)
But it fails with different kinds of errors. Currently this:
File "/usr/local/lib/python3.10/dist-packages/diffusers/models/unets/unet_2d_condition.py", line 973, in get_aug_embed
if "text_embeds" not in added_cond_kwargs:
TypeError: argument of type 'NoneType' is not iterable
Is this the wrong approach? Can I even take a diffuser model and fine tune it like this?