Instructions to use CarolineM5/InstructPix2Pix_WithoutPrompt_4_faces with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CarolineM5/InstructPix2Pix_WithoutPrompt_4_faces with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CarolineM5/InstructPix2Pix_WithoutPrompt_4_faces", 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:
- b2954516ca6b644458b3ad1ed1ebd1b05435bbe2b0a973c2692238bd1466edee
- Size of remote file:
- 4.79 GB
- SHA256:
- 4ddd8066961c86713f290f3bdccd69b0e3a545187ebb7bb3a384e74899dd5863
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.