Try Google Gemini Omni Flash Video Generator from Google →
Models
Agents
WorkflowsStudioPricingBlogDocs
ExploreDiscover models by categoryBrowse All ModelsBrowse the complete catalogSee FavoritesSign in to view saved models
OverviewThe platform at a glanceLearnSkills, knowledge, guardrailsAnatomyWhat makes agents reasonBuild Your AgentPick skills, set tier, deploy
Pre-built AgentsBrowse the catalog
Agent Usecases
Ad Campaign ManagerApp Event ManagerApp Review RepliesBarber BookingCustomer Win-BackEcommerce ListingsRestaurant Reviews
Sign InStart Building

Task History

Click to see output list

No tasks yet

Go to Models
Explore models/
Active

diffusers / stable-diffusion-xl-1.0-inpainting-0.1

stable-diffusion-xl-1.0-inpainting-0.1

bydiffusers

SD-XL Inpainting 0.1 is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask.

SdxlInpaintingFp32
Model ID
stable-diffusion-xl-1.0-inpainting-0.1
Provider
diffusers
Added
1697739381
stable-diffusion-xl-1.0-inpainting-0.1
0
Comments
Average rating : 0 (0 users)
Providerdiffusers
Modelstable-diffusion-xl-1.0-inpainting-0.1
SdxlInpaintingFp32
wiro playground—diffusers/stable-diffusion-xl-1.0-inpainting-0.1
Reset to defaults

Choose an image that will re-generate

Enter one or more image URLs separated by commas for re-generation. Make sure the URLs are accessible.

Reverse colors

Choose an image mask that will re-generate

Choose one or more image mask URLs separated by commas that will be used for re-generation. Make sure the URLs are accessible.

Tell us about any details you want to generate

Specify things to not see in the output

Sample outputs
Sample 1
Sample 2
Sample 3
Sample 4
Added 1697739381
SD-XL Inpainting 0.1 is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask. The SD-XL Inpainting 0.1 was initialized with the stable-diffusion-xl-base-1.0 weights. The model is trained for 40k steps at resolution 1024x1024 and 5% dropping of the text-conditioning to improve classifier-free classifier-free guidance sampling. For inpainting, the UNet has 5 additional input channels (4 for the encoded masked-image and 1 for the mask itself) whose weights were zero-initialized after restoring the non-inpainting checkpoint. During training, we generate synthetic masks and, in 25% mask everything.

API quick start

Run stable-diffusion-xl-1.0-inpainting-0.1 with a single API call.

POST https://api.wiro.ai/v1/Run/diffusers/stable-diffusion-xl-1.0-inpainting-0.1
{
  "prompt": "handsome man with sunglasses, realistic, …",
  "inputImage": "https://your-cdn.com/input.png",
  "inputImageUrl": "...",
  "inputImageMask": "https://your-cdn.com/input.png"
}
View full API docs

Discover, test, and run AI models, build workflows and agents with one unified API.

All systems operational
WiroAboutBlogCareersContact
ProductModelsAgentsPricingPartnerChangelogStatusFAQ
Getting StartedIntroductionAuthenticationProjectsCode ExamplesWiro MCP ServerSelf-Hosted MCPn8n IntegrationLLMs.txt
API ReferenceModelsRun a ModelModel ParametersTasksLLM & Chat StreamingWebSocketRealtime VoiceFiles
© 2026 Wiro AI. All rights reserved.
PrivacyTermsData Deletion