Any-to-Any
Transformers
Diffusers
Safetensors
English
llada2_moe
feature-extraction
multimodal
image-generation
image-understanding
image-editing
diffusion
Mixture of Experts
text-to-image
custom_code
Instructions to use inclusionAI/LLaDA2.0-Uni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inclusionAI/LLaDA2.0-Uni with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("inclusionAI/LLaDA2.0-Uni", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 6a6e9ad0fdd4ed52b8174eb32e89c9b55bd9a2badbca12bdcc4963e026062866
- Size of remote file:
- 1.26 MB
- SHA256:
- b93b777561b5217b2545a85e02698d64c246e502c8fa6e15b86b1203da01138e
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