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
Update README.md
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README.md
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## Quick Start
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> **Note:** Full installation instructions and CLI scripts are available in the [GitHub repository](https://github.com/inclusionAI/LLaDA2-Uni).
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### βοΈ Installation
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#### 1. Create a conda environment
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```bash
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git clone https://github.com/inclusionAI/LLaDA2-Uni && cd LLaDA2-Uni
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conda create -n llada2_uni python=3.10 -y
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conda activate llada2_uni
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```
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## Repository Structure
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```
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LLaDA2-Uni/
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βββ config.json # Model configuration
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βββ modeling_llada2uni_moe.py # Model implementation (trust_remote_code)
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βββ configuration_llada2uni_moe.py # Config class
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## Quick Start
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> **Note:** Full installation instructions and CLI scripts are available in the [GitHub repository](https://github.com/inclusionAI/LLaDA2.0-Uni).
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### βοΈ Installation
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#### 1. Create a conda environment
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```bash
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git clone https://github.com/inclusionAI/LLaDA2.0-Uni && cd LLaDA2.0-Uni
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conda create -n llada2_uni python=3.10 -y
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conda activate llada2_uni
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```
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## Repository Structure
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```
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LLaDA2.0-Uni/
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βββ config.json # Model configuration
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βββ modeling_llada2uni_moe.py # Model implementation (trust_remote_code)
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βββ configuration_llada2uni_moe.py # Config class
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