Instructions to use UnicomAI/UniT2IXL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use UnicomAI/UniT2IXL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("UnicomAI/UniT2IXL", 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:
- af42a565bf6922ca34ba2c2f1e05e3f08364679a8e11d4b9f0f5ffa303c100a3
- Size of remote file:
- 1.3 GB
- SHA256:
- 52cdcef35ebe27502fb919c2e6cf0b72ed3b5119d0f899aee1586b53d309e27f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.