Instructions to use baricevic/instruct-pix2pix-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use baricevic/instruct-pix2pix-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("baricevic/instruct-pix2pix-model", 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
- Xet hash:
- eebc206f2f23208c477c42caec7cfc61fb3ab51f671def3c6854cb378c9761d7
- Size of remote file:
- 3.44 GB
- SHA256:
- dde0f0048a971823b359c6c191b8ffc41fe67e7f3642de3d580ae1a80b38a60c
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