Instructions to use inclusionAI/LLaDA-MoE-7B-A1B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inclusionAI/LLaDA-MoE-7B-A1B-Base with Transformers:

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

pipe = pipeline("text-generation", model="inclusionAI/LLaDA-MoE-7B-A1B-Base", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("inclusionAI/LLaDA-MoE-7B-A1B-Base", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use inclusionAI/LLaDA-MoE-7B-A1B-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inclusionAI/LLaDA-MoE-7B-A1B-Base"
# 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/LLaDA-MoE-7B-A1B-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/inclusionAI/LLaDA-MoE-7B-A1B-Base

SGLang

How to use inclusionAI/LLaDA-MoE-7B-A1B-Base 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/LLaDA-MoE-7B-A1B-Base" \
    --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/LLaDA-MoE-7B-A1B-Base",
		"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/LLaDA-MoE-7B-A1B-Base" \
        --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/LLaDA-MoE-7B-A1B-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use inclusionAI/LLaDA-MoE-7B-A1B-Base with Docker Model Runner:
```
docker model run hf.co/inclusionAI/LLaDA-MoE-7B-A1B-Base
```

luguoshan commited on Oct 28, 2025

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@@ -21,6 +21,7 @@ This model is based on the principles described in the paper [Large Language Dif
 - `LLaDA-MoE-7B-A1B-Base`: A base pre-trained model designed for research and secondary development.
 - `LLaDA-MoE-7B-A1B-Instruct`: An instruction-tuned model optimized for practical applications.
 ---
 <div align="center">
@@ -56,6 +57,7 @@ This model is based on the principles described in the paper [Large Language Dif
 |--------|-------------|-------------------|
 | [`inclusionAI/LLaDA-MoE-7B-A1B-Base`](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Base) | Base pre-trained model for research and fine-tuning. | [🤗 Model Card](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Base) |
 | [`inclusionAI/LLaDA-MoE-7B-A1B-Instruct`](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Instruct) | Instruction-tuned model, ready for downstream applications. | [🤗 Model Card](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Instruct) |
 ---

 - `LLaDA-MoE-7B-A1B-Base`: A base pre-trained model designed for research and secondary development.
 - `LLaDA-MoE-7B-A1B-Instruct`: An instruction-tuned model optimized for practical applications.
+- `LLaDA-MoE-7B-A1B-Instruct-TD`: A specialized instruction-tuned model, further optimized for accelerated inference using Trajectory Distillation.
 ---
 <div align="center">
 |--------|-------------|-------------------|
 | [`inclusionAI/LLaDA-MoE-7B-A1B-Base`](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Base) | Base pre-trained model for research and fine-tuning. | [🤗 Model Card](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Base) |
 | [`inclusionAI/LLaDA-MoE-7B-A1B-Instruct`](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Instruct) | Instruction-tuned model, ready for downstream applications. | [🤗 Model Card](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Instruct) |
+| [`inclusionAI/LLaDA-MoE-7B-A1B-Instruct-TD`](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Instruct-TD) | An instruction-tuned model further optimized with **Trajectory Distillation (TD)** for accelerated inference. Decodes multiple tokens per forward pass. | [🤗 Model Card](https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Instruct-TD) |
 ---