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:
- 4736ad01b8bd989bde3fc1fb4cbb7051ce87e3014bd39a7ee4bcb14459ff41fb
- Size of remote file:
- 246 MB
- SHA256:
- 38aca8345bad31819530d6291463fe6b38b07275ae38065f774b30e7a8e07d64
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