Text-to-Image
Diffusers
Safetensors
ErnieImagePipeline
ernie-image
nunchaku
bitsandbytes
quantized
int4
nf4
4bit
8B
8-bit precision
Instructions to use lite-infer/ERNIE-Image-Turbo-nunchaku-lite-int4-bnb4-text-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lite-infer/ERNIE-Image-Turbo-nunchaku-lite-int4-bnb4-text-encoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lite-infer/ERNIE-Image-Turbo-nunchaku-lite-int4-bnb4-text-encoder", 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:
- 6dfe81ec031e8a6cd907b14841b1e3f1eb6c948f65f6294d4e875f7f569a4f60
- Size of remote file:
- 1.48 MB
- SHA256:
- 0763bbc77b2abd5edbfdac51c7bb2471d8eeecc02df1503b2e91fb034b22938e
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