Instructions to use JCTN/InstantID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JCTN/InstantID with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JCTN/InstantID", 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

- Xet hash:
- 670570730c1a62fab5a57678db955a8a936a9138a85b93e5d9c4dd7277f2e74d
- Size of remote file:
- 8.47 MB
- SHA256:
- f20e80f08c8efd2ac74ed93070851bea677489643dee8a28912fcd06b56348d2
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