Instructions to use inclusionAI/LLaDA2.0-mini-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inclusionAI/LLaDA2.0-mini-preview with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="inclusionAI/LLaDA2.0-mini-preview", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("inclusionAI/LLaDA2.0-mini-preview", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use inclusionAI/LLaDA2.0-mini-preview with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inclusionAI/LLaDA2.0-mini-preview"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inclusionAI/LLaDA2.0-mini-preview",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/inclusionAI/LLaDA2.0-mini-preview

SGLang

How to use inclusionAI/LLaDA2.0-mini-preview with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "inclusionAI/LLaDA2.0-mini-preview" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inclusionAI/LLaDA2.0-mini-preview",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "inclusionAI/LLaDA2.0-mini-preview" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inclusionAI/LLaDA2.0-mini-preview",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use inclusionAI/LLaDA2.0-mini-preview with Docker Model Runner:
```
docker model run hf.co/inclusionAI/LLaDA2.0-mini-preview
```

lccurious commited on Oct 17, 2025

Commit

e8bf25c

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1 Parent(s): f122008

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@@ -1,3 +1,12 @@
 # LLaDA2-mini-preview
 **LLaDA2-mini-preview** is a diffusion language model featuring a 16BA1B Mixture-of-Experts (MoE) architecture. As an enhanced, instruction-tuned iteration of the LLaDA series, it is optimized for practical applications.
@@ -277,5 +286,4 @@ This project is licensed under the terms of the [Apache License 2.0](https://www
 ## 🤝 Contact & Collaboration
 For questions, collaborations, or feedback, please reach out via [Hugging Face](https://huggingface.co/inclusionAI/LLaDA2.0-mini-preview) or open an issue in the [repository](https://github.com/inclusionAI).
-👉 Join us in advancing open, efficient, and intelligent language models!

+---
+license: apache-2.0
+library_name: transformers
+tags:
+- dllm
+- diffusion
+- llm
+- text_generation
+---
 # LLaDA2-mini-preview
 **LLaDA2-mini-preview** is a diffusion language model featuring a 16BA1B Mixture-of-Experts (MoE) architecture. As an enhanced, instruction-tuned iteration of the LLaDA series, it is optimized for practical applications.
 ## 🤝 Contact & Collaboration
 For questions, collaborations, or feedback, please reach out via [Hugging Face](https://huggingface.co/inclusionAI/LLaDA2.0-mini-preview) or open an issue in the [repository](https://github.com/inclusionAI).
+👉 Join us in advancing open, efficient, and intelligent language models!