Model Card for Model ID

Model Details

Model Description

StableDiffusion3 model trained with the UltraEdit data to perform the mask-based and free-form image editing.

You can get the modified verson of diffusers from the github PAGE:

cd diffusers && pip install -e .

And then you can run:

# For Editing with SD3
import torch
from diffusers import StableDiffusion3InstructPix2PixPipeline
from diffusers.utils import load_image
import requests
import PIL.Image

pipe = StableDiffusion3InstructPix2PixPipeline.from_pretrained("BleachNick/SD3_UltraEdit_w_mask", torch_dtype=torch.float16)
pipe = pipe.to("cuda")
prompt="What if the horse wears a hat?"
img = load_image("input.png").resize((512, 512))
mask_img = load_image("mask_img.png").resize(img.size)
# For free form Editing, seed a blank mask
# mask_img = PIL.Image.new("RGB", img.size, (255, 255, 255))
image = pipe(
    prompt,
    image=img,
    mask_img=mask_img,
    negative_prompt="",
    num_inference_steps=50,
    image_guidance_scale=1.5,
    guidance_scale=7.5,
).images[0]
image.save("edited_image.png")
# display image

• Developed by: [More Information Needed]
• Funded by [optional]: [More Information Needed]
• Shared by [optional]: [More Information Needed]
• Model type: [More Information Needed]
• Language(s) (NLP): [More Information Needed]
• License: [More Information Needed]
• Finetuned from model [optional]: [More Information Needed]

Model Sources [optional]

• Repository: [More Information Needed]
• Paper [optional]: [More Information Needed]
• Demo [optional]: [More Information Needed]

Uses

Direct Use

[More Information Needed]

Downstream Use [optional]

[More Information Needed]

Out-of-Scope Use

[More Information Needed]

Bias, Risks, and Limitations

[More Information Needed]

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

Training Details

Training Data

[More Information Needed]

Training Procedure

Preprocessing [optional]

[More Information Needed]

Training Hyperparameters

• Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

[More Information Needed]

Evaluation

Testing Data, Factors & Metrics

Testing Data

[More Information Needed]

Factors

[More Information Needed]

Metrics

[More Information Needed]

Results

[More Information Needed]

Summary

Model Examination [optional]

[More Information Needed]

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• Hardware Type: [More Information Needed]
• Hours used: [More Information Needed]
• Cloud Provider: [More Information Needed]
• Compute Region: [More Information Needed]
• Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

[More Information Needed]

Compute Infrastructure

[More Information Needed]

Hardware

[More Information Needed]

Software

[More Information Needed]

Citation [optional]

BibTeX:

[More Information Needed]

APA:

[More Information Needed]

Glossary [optional]

[More Information Needed]

More Information [optional]

[More Information Needed]

Model Card Authors [optional]

[More Information Needed]

Model Card Contact

[More Information Needed]