2ad0752582
- Rename old "model_management" directory to "model_management_OLD" in order to catch dangling references to original model manager. - Caught and fixed most dangling references (still checking) - Rename lora, textual_inversion and model_patcher modules - Introduce a RawModel base class to simplfy the Union returned by the model loaders. - Tidy up the model manager 2-related tests. Add useful fixtures, and a finalizer to the queue and installer fixtures that will stop the services and release threads. |
||
|---|---|---|
| .. | ||
| __init__.py | ||
| attention_processor.py | ||
| ip_adapter.py | ||
| ip_attention_weights.py | ||
| README.md | ||
| resampler.py | ||
| unet_patcher.py | ||
IP-Adapter Model Formats
The official IP-Adapter models are released here: 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:
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:
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 repo.
InvokeAI Hosted IP-Adapters
Image Encoders:
IP-Adapters: