Text-to-Image
Diffusers
Safetensors
ErnieImagePipeline
ernie-image
nunchaku
bitsandbytes
quantized
nvfp4
nf4
4bit
8B
8-bit precision
Instructions to use lite-infer/ERNIE-Image-Turbo-nunchaku-lite-nvfp4-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-nvfp4-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-nvfp4-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:
- 26c8a74c71febfd6287bbc6aaf206d7ffeafc6ae1380c3b5408aa957bd4271f5
- Size of remote file:
- 1.43 MB
- SHA256:
- 18c7c2bfb7c646485bacf6723af99f4941422dd93e989680da0d91b8050f2339
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