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, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d1415dc49ae9b8f3f7ea3fddc7011f765e98c75be88b5f72bf9f0af47d7e8ba
- Size of remote file:
- 12.3 GB
- SHA256:
- b4538abc88dc41ecbdced5b032a5f0ac1f0780f96b36256d37bb7a105930ae8f
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