Instructions to use ixim/ERNIE-Image-INT8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ixim/ERNIE-Image-INT8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ixim/ERNIE-Image-INT8", 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
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- f8d8b5db81cf392b495acd34f4b81768b081994860086fd01208a23dd1842c6d
- Size of remote file:
- 490 kB
- SHA256:
- cbc21bad4fd3c805f5d49a16d67e79d6b2d4d5e8e6099b3cadf23866cbb0bec9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.