Instructions to use h94/IP-Adapter-FaceID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use h94/IP-Adapter-FaceID with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("h94/IP-Adapter-FaceID", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download ip-adapter-faceid_sdxl.bin from h94/IP-Adapter-FaceID: direct link, hf CLI and curl.
- Browser
- Download file 1.07 GB
-
https://huggingface.co/h94/IP-Adapter-FaceID/resolve/main/ip-adapter-faceid_sdxl.bin
- Command line
-
hf download hf://h94/IP-Adapter-FaceID/ip-adapter-faceid_sdxl.bin
-
curl -L -o ip-adapter-faceid_sdxl.bin https://huggingface.co/h94/IP-Adapter-FaceID/resolve/main/ip-adapter-faceid_sdxl.bin
1.07 GB
- Xet hash:
- b924b678ef4ca408577e51faa08a4d281e3411fca24cb84a080a3751d65ed697
- Size of remote file:
- 1.07 GB
- SHA256:
- f455fed24e207c878ec1e0466b34a969d37bab857c5faa4e8d259a0b4ff63d7e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.