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

Libraries

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

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

pipe = pipeline("text-generation", model="inclusionAI/LLaDA2.0-mini", 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", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use inclusionAI/LLaDA2.0-mini 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"
# 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",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

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

SGLang

How to use inclusionAI/LLaDA2.0-mini 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" \
    --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",
		"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" \
        --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",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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

LLaDA2.0-mini

Commit History

Insert tracking points on the ModelCard to track visit statistics

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xiaoyayaya commited on Apr 13

Fix: Align mask preparation logic for Eager attention to prevent corrupted outputs (#4)

d23215a

utdawn

haibo8 commited on Feb 9

Update README.md

1856dc4
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utdawn commited on Dec 19, 2025

Update README.md

d699e90
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utdawn commited on Nov 26, 2025

Update README.md

5e97d1a
verified

utdawn commited on Nov 25, 2025

First model version

1b8bc9e

lccurious commited on Nov 25, 2025

initial commit

09ff5ec
verified

utdawn commited on Nov 25, 2025

Commit History

Insert tracking points on the ModelCard to track visit statistics a56b484 verified

Fix: Align mask preparation logic for Eager attention to prevent corrupted outputs (#4) d23215a

Update README.md 1856dc4 verified

Update README.md d699e90 verified

Update README.md 5e97d1a verified

First model version 1b8bc9e

initial commit 09ff5ec verified