Text-to-Image
Diffusers
Safetensors
English
Chinese
LLaDAImagePipeline
image-generation
image-editing
image-to-image
Instructions to use inclusionAI/LLaDA-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use inclusionAI/LLaDA-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("inclusionAI/LLaDA-Image", 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:
- b32cc13f4cb27e706ba2527a749e1668c5af6f37b9c719ece9821c91fc8f6314
- Size of remote file:
- 2.91 GB
- SHA256:
- 49833bce9b494bb38b41cc09c0d1fa524049a5453c44281aa6f5d6d68c2b0b0b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.