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
kenshin commited on
Commit ·
e4e2703
1
Parent(s): f1c37d4
docs: add turbo sampling note
Browse files
README.md
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Use the Turbo checkpoint for fast generation and editing. Its recommended sampling configuration is **4 steps**.
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```python
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import torch
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Use the Turbo checkpoint for fast generation and editing. Its recommended sampling configuration is **4 steps**.
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> [!NOTE]
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> For LLaDA-Image-Turbo inference, you can try setting `stochastic_sampling` to `false` in `scheduler/scheduler_config.json`, which may produce sharper details in some cases.
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```python
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import torch
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