Instructions to use AltLuv/text-to-image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AltLuv/text-to-image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AltLuv/text-to-image", 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:
- a25ef2b578744dc8ba06d80f05270e140aee778dc38202ea55da3d842f2474fe
- Size of remote file:
- 3.44 GB
- SHA256:
- f08f339092cf1629a110983a80c95ef2b60a33aaf677689f6a520a9f5dc171a0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.