[IP-Adapter](https://ip-adapter.github.io/) is a lightweight adapter that enables image prompting for any diffusion model. This adapter works by decoupling the cross-attention layers of the image and text features. All the other model components are frozen and only the embedded image features in the UNet are trained. As a result, IP-Adapter files are typically only ~100MBs.  
You can learn more about how to use IP-Adapter for different tasks and specific use cases in the [IP-Adapter](../using-diffusers/ip_adapter) guide.  
> [!TIP]
> Diffusers currently only supports IP-Adapter for some of the most popular pipelines. Feel free to open a feature request if you have a cool use case and want to integrate IP-Adapter with an unsupported pipeline!
> Official IP-Adapter checkpoints are available from [h94/IP-Adapter](https://huggingface.co/h94/IP-Adapter).  
To start, load a Stable Diffusion checkpoint.  
```py
from diffusers import AutoPipelineForText2Image
import torch
from diffusers.utils import load_image

pipeline = AutoPipelineForText2Image.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16).to("cuda")
```  
Then load the IP-Adapter weights and add it to the pipeline with the [`~loaders.IPAdapterMixin.load_ip_adapter`] method.  
```py
pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin")
```  
Once loaded, you can use the pipeline with an image and text prompt to guide the image generation process.  
```py
image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/load_neg_embed.png")
generator = torch.Generator(device="cpu").manual_seed(33)
images = pipeline(
prompt='best quality, high quality, wearing sunglasses',
ip_adapter_image=image,
negative_prompt="monochrome, lowres, bad anatomy, worst quality, low quality",
num_inference_steps=50,
generator=generator,
).images[0]
images
```  
<div class="flex justify-center">
<img src="https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/ip-bear.png" />
</div>
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/using-diffusers/loading_adapters.md