Instructions to use jpawan33/instruct-pix2pix-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jpawan33/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("jpawan33/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:
- 652d45e3ccbd17a556981cf0902a2ada348d6fd1919b2b3d41022eb1e9d18cd7
- Size of remote file:
- 3.46 GB
- SHA256:
- e110819e79627ae260e1e8c8decdb6f08e6c5e8e8ce50bec68822e03543539dc
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