Instructions to use inclusionAI/LLaDA2.1-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inclusionAI/LLaDA2.1-mini with Transformers:

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

pipe = pipeline("text-generation", model="inclusionAI/LLaDA2.1-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/LLaDA2.1-mini", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use inclusionAI/LLaDA2.1-mini with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inclusionAI/LLaDA2.1-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/LLaDA2.1-mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/inclusionAI/LLaDA2.1-mini

SGLang

How to use inclusionAI/LLaDA2.1-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/LLaDA2.1-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/LLaDA2.1-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/LLaDA2.1-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/LLaDA2.1-mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use inclusionAI/LLaDA2.1-mini with Docker Model Runner:
```
docker model run hf.co/inclusionAI/LLaDA2.1-mini
```

utdawn commited on Feb 12

Commit

bbb5715

verified ·

1 Parent(s): c38df8b

Update README.md

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README.md CHANGED Viewed

@@ -40,7 +40,7 @@ tags:
 <td align="center">61.59</td>
 <td align="center">64.72</td>
 <td align="center">63.39 | 2.60</td>
-<td align="center">62.24 | 5.34</td>
 <td align="center">63.90 | 3.12</td>
 </tr>
 <tr><td colspan="6" align="center"><b>Knowledge</b></td></tr>
@@ -203,14 +203,14 @@ tags:
 <td align="center">72.69</td>
 <td align="center">77.25</td>
 <td align="center">78.24 | 3.43</td>
-<td align="center">78.84 | 10.59</td>
 <td align="center">74.07 | 6.30</td>
 </tr>
 <tr>
 <td align="left">HumanEval+</td>
 <td align="center">79.5</td>
 <td align="center">80.03</td>
-<td align="center">81.71 | 5.16</td>
 <td align="center">80.49 | 12.32</td>
 <td align="center">82.93 | 7.77</td>
 </tr>
@@ -231,14 +231,6 @@ tags:
 <td align="center">34.39 | 4.09</td>
 </tr>
 <tr>
-<td align="left">Aider</td>
-<td align="center">55.64</td>
-<td align="center">49.62</td>
-<td align="center">39.85 | 3.57</td>
-<td align="center">43.61 | 8.11</td>
-<td align="center">45.11 | 4.85</td>
-</tr>
-<tr>
 <td align="left">BIRD-SQL</td>
 <td align="center">36.11</td>
 <td align="center">39.67</td>
@@ -313,14 +305,6 @@ tags:
 <td align="center">73.61 | 5.14</td>
 </tr>
 <tr>
-<td align="left">CodeIF-Bench</td>
-<td align="center">50.00</td>
-<td align="center">46.00</td>
-<td align="center">46.00 | 2.62</td>
-<td align="center">42.00 | 6.68</td>
-<td align="center">48.00 | 3.62</td>
-</tr>
-<tr>
 <td align="left">Nexus FC</td>
 <td align="center">37.71</td>
 <td align="center">34.38</td>

 <td align="center">61.59</td>
 <td align="center">64.72</td>
 <td align="center">63.39 | 2.60</td>
+<td align="center">62.07 | 5.34</td>
 <td align="center">63.90 | 3.12</td>
 </tr>
 <tr><td colspan="6" align="center"><b>Knowledge</b></td></tr>
 <td align="center">72.69</td>
 <td align="center">77.25</td>
 <td align="center">78.24 | 3.43</td>
+<td align="center">73.28 | 10.59</td>
 <td align="center">74.07 | 6.30</td>
 </tr>
 <tr>
 <td align="left">HumanEval+</td>
 <td align="center">79.5</td>
 <td align="center">80.03</td>
+<td align="center">81.40 | 5.16</td>
 <td align="center">80.49 | 12.32</td>
 <td align="center">82.93 | 7.77</td>
 </tr>
 <td align="center">34.39 | 4.09</td>
 </tr>
 <tr>
 <td align="left">BIRD-SQL</td>
 <td align="center">36.11</td>
 <td align="center">39.67</td>
 <td align="center">73.61 | 5.14</td>
 </tr>
 <tr>
 <td align="left">Nexus FC</td>
 <td align="center">37.71</td>
 <td align="center">34.38</td>