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
- Draw Things
- DiffusionBee
How to use LoRA correctly?
First of all, thank you for your great work. It seems to me, that any lora scale besides 0.1 or less just makes the resulting image worse. Any tips on using it?
I would also very much appreciate it, if you would share the parameters you used for the demo results
First of all, thank you for your great work. It seems to me, that any lora scale besides 0.1 or less just makes the resulting image worse. Any tips on using it?
have you used the code in "README" to test?
First of all, thank you for your great work. It seems to me, that any lora scale besides 0.1 or less just makes the resulting image worse. Any tips on using it?
have you used the code in "README" to test?
Yes, I did and it works good enough, however I see no use of LoRA there
hi, the demo in "README" has used LORA. https://github.com/tencent-ailab/IP-Adapter/blob/main/ip_adapter/ip_adapter_faceid.py#L71-L80
I will update the code soon, and you can use a normal ip-adapter + normal LORA, just as https://github.com/cubiq/ComfyUI_IPAdapter_plus/issues/145
Once again, thank you for your work!