The official IP-Adapter models are released here: [h94/IP-Adapter](https://huggingface.co/h94/IP-Adapter)
This official model repo does not integrate well with InvokeAI's current approach to model management, so we have defined a new file structure for IP-Adapter models. The InvokeAI format is described below.
## CLIP Vision Models
CLIP Vision models are organized in `diffusers`` format. The expected directory structure is:
```bash
ip_adapter_sd_image_encoder/
├── config.json
└── model.safetensors
```
## IP-Adapter Models
IP-Adapter models are stored in a directory containing two files
-`image_encoder.txt`: A text file containing the model identifier for the CLIP Vision encoder that is intended to be used with this IP-Adapter model.
-`ip_adapter.bin`: The IP-Adapter weights.
Sample directory structure:
```bash
ip_adapter_sd15/
├── image_encoder.txt
└── ip_adapter.bin
```
### Why save the weights in a .safetensors file?
The weights in `ip_adapter.bin` are stored in a nested dict, which is not supported by `safetensors`. This could be solved by splitting `ip_adapter.bin` into multiple files, but for now we have decided to maintain consistency with the checkpoint structure used in the official [h94/IP-Adapter](https://huggingface.co/h94/IP-Adapter) repo.
