Instructions to use jaxmetaverse/all_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jaxmetaverse/all_models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jaxmetaverse/all_models", torch_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:
- c750d848c73d20b225b0ce9a949295f8c0741a1dc325f5413538f29cc4589cc6
- Size of remote file:
- 827 MB
- SHA256:
- f5cd815510908284eca7c5b9e81bdd63fc4cbef761f83bfb8fbe5e2880b2b830
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.