SD3.5-Large-IP-Adapter

This repository contains a IP-Adapter for SD3.5-Large model released by researchers from InstantX Team, where image work just like text, so it may not be responsive or interfere with other text, but we do hope you enjoy this model, have fun and share your creative works with us on Twitter.

Model Card

This is a regular IP-Adapter, where the new layers are added into all 38 blocks. We use google/siglip-so400m-patch14-384 to encode image for its superior performance, and adopt a TimeResampler to project. The image token number is set to 64.

Showcases

Inference

The code has not been integrated into diffusers yet, please use our local files at this moment.

Python

import torch
from PIL import Image

from models.transformer_sd3 import SD3Transformer2DModel
from pipeline_stable_diffusion_3_ipa import StableDiffusion3Pipeline

model_path = 'stabilityai/stable-diffusion-3.5-large'
ip_adapter_path = './ip-adapter.bin'
image_encoder_path = "google/siglip-so400m-patch14-384"

transformer = SD3Transformer2DModel.from_pretrained(
    model_path, subfolder="transformer", torch_dtype=torch.bfloat16
)

pipe = StableDiffusion3Pipeline.from_pretrained(
    model_path, transformer=transformer, torch_dtype=torch.bfloat16
).to("cuda")

pipe.init_ipadapter(
    ip_adapter_path=ip_adapter_path, 
    image_encoder_path=image_encoder_path, 
    nb_token=64, 
)

ref_img = Image.open('./assets/1.jpg').convert('RGB')

# please note that SD3.5 Large is sensitive to highres generation like 1536x1536
image = pipe(
    width=1024,
    height=1024,
    prompt='a cat',
    negative_prompt="lowres, low quality, worst quality",
    num_inference_steps=24, 
    guidance_scale=5.0,
    generator=torch.Generator("cuda").manual_seed(42),
    clip_image=ref_img,
    ipadapter_scale=0.5,
).images[0]
image.save('./result.jpg')

Community ComfyUI Support

Please refer to Slickytail/ComfyUI-InstantX-IPAdapter-SD3.

License

The model is released under stabilityai-ai-community. All copyright reserved.

Acknowledgements

This project is sponsored by HuggingFace and fal.ai. Thanks to Slickytail for supporting ComfyUI node.

Citation

If you find this project useful in your research, please cite us via

INI

@misc{sd35-large-ipa,
    author = {InstantX Team},
    title = {InstantX SD3.5-Large IP-Adapter Page},
    year = {2024},
}

Inference

The code has not been integrated into diffusers yet, please use our local files at this moment.

Python

import torch
from PIL import Image

from models.transformer_sd3 import SD3Transformer2DModel
from pipeline_stable_diffusion_3_ipa import StableDiffusion3Pipeline

model_path = 'stabilityai/stable-diffusion-3.5-large'
ip_adapter_path = './ip-adapter.bin'
image_encoder_path = "google/siglip-so400m-patch14-384"

transformer = SD3Transformer2DModel.from_pretrained(
    model_path, subfolder="transformer", torch_dtype=torch.bfloat16
)

pipe = StableDiffusion3Pipeline.from_pretrained(
    model_path, transformer=transformer, torch_dtype=torch.bfloat16
).to("cuda")

pipe.init_ipadapter(
    ip_adapter_path=ip_adapter_path, 
    image_encoder_path=image_encoder_path, 
    nb_token=64, 
)

ref_img = Image.open('./assets/1.jpg').convert('RGB')

# please note that SD3.5 Large is sensitive to highres generation like 1536x1536
image = pipe(
    width=1024,
    height=1024,
    prompt='a cat',
    negative_prompt="lowres, low quality, worst quality",
    num_inference_steps=24, 
    guidance_scale=5.0,
    generator=torch.Generator("cuda").manual_seed(42),
    clip_image=ref_img,
    ipadapter_scale=0.5,
).images[0]
image.save('./result.jpg')

SD3.5 Large IP Adapter