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mirror of https://github.com/huggingface/diffusers.git synced 2026-01-27 17:22:53 +03:00

Move IP Adapter Face ID to core (#7186)

* Switch to peft and multi proj layers

* Move Face ID loading and inference to core

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
This commit is contained in:
Fabio Rigano
2024-04-19 02:13:27 +02:00
committed by GitHub
parent e23c27e905
commit b5c8b555d7
10 changed files with 595 additions and 378 deletions

View File

@@ -320,3 +320,40 @@ pipeline = AutoPipelineForText2Image.from_pretrained(
pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="sdxl_models", weight_name="ip-adapter-plus_sdxl_vit-h.safetensors")
```
### IP-Adapter Face ID models
The IP-Adapter FaceID models are experimental IP Adapters that use image embeddings generated by `insightface` instead of CLIP image embeddings. Some of these models also use LoRA to improve ID consistency.
You need to install `insightface` and all its requirements to use these models.
<Tip warning={true}>
As InsightFace pretrained models are available for non-commercial research purposes, IP-Adapter-FaceID models are released exclusively for research purposes and are not intended for commercial use.
</Tip>
```py
pipeline = AutoPipelineForText2Image.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16
).to("cuda")
pipeline.load_ip_adapter("h94/IP-Adapter-FaceID", subfolder=None, weight_name="ip-adapter-faceid_sdxl.bin", image_encoder_folder=None)
```
If you want to use one of the two IP-Adapter FaceID Plus models, you must also load the CLIP image encoder, as this models use both `insightface` and CLIP image embeddings to achieve better photorealism.
```py
from transformers import CLIPVisionModelWithProjection
image_encoder = CLIPVisionModelWithProjection.from_pretrained(
"laion/CLIP-ViT-H-14-laion2B-s32B-b79K",
torch_dtype=torch.float16,
)
pipeline = AutoPipelineForText2Image.from_pretrained(
"runwayml/stable-diffusion-v1-5",
image_encoder=image_encoder,
torch_dtype=torch.float16
).to("cuda")
pipeline.load_ip_adapter("h94/IP-Adapter-FaceID", subfolder=None, weight_name="ip-adapter-faceid-plus_sd15.bin")
```