Text-to-Image
Diffusers
nunchaku-lite
diffuse-compressor
quantized
ernie-image
ernie-image-turbo
svdquant
int4
fp4
Instructions to use rootonchair/ERNIE-Image-Turbo-nunchaku-lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rootonchair/ERNIE-Image-Turbo-nunchaku-lite with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rootonchair/ERNIE-Image-Turbo-nunchaku-lite", 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:
- 2c37c31f353d232e279dec2b729986d16c0b36e90dc6b97f8db372b86848dc61
- Size of remote file:
- 1.84 MB
- SHA256:
- 0caf56eca8f0dea4878fdfa1d245e6dff9f4f37f4724be020819b36611c39243
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