Instructions to use OpenMOSS-Team/DiRL-8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OpenMOSS-Team/DiRL-8B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="OpenMOSS-Team/DiRL-8B-Instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("OpenMOSS-Team/DiRL-8B-Instruct", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use OpenMOSS-Team/DiRL-8B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OpenMOSS-Team/DiRL-8B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OpenMOSS-Team/DiRL-8B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/OpenMOSS-Team/DiRL-8B-Instruct

SGLang

How to use OpenMOSS-Team/DiRL-8B-Instruct 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 "OpenMOSS-Team/DiRL-8B-Instruct" \
    --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": "OpenMOSS-Team/DiRL-8B-Instruct",
		"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 "OpenMOSS-Team/DiRL-8B-Instruct" \
        --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": "OpenMOSS-Team/DiRL-8B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use OpenMOSS-Team/DiRL-8B-Instruct with Docker Model Runner:
```
docker model run hf.co/OpenMOSS-Team/DiRL-8B-Instruct
```

Auraithm

nielsr HF Staff commited on Dec 31, 2025

Commit

89225da

verified ·

1 Parent(s): f1fbf4d

Add pipeline_tag and library_name to metadata (#1)

Browse files

- Add pipeline_tag and library_name to metadata (14b37d7dc5854031849b2f23e9404ea7a89aad53)

Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +3 -1

README.md CHANGED Viewed

@@ -1,4 +1,5 @@
 ---
 language:
 - en
 - zh
@@ -7,8 +8,9 @@ tags:
 - math
 - reasoning
 - diffusion
-base_model: JetLM/SDAR-8B-Chat
 model_type: sdar
 ---
 <h1 align="center">DiRL-8B-Instruct</h1>

 ---
+base_model: JetLM/SDAR-8B-Chat
 language:
 - en
 - zh
 - math
 - reasoning
 - diffusion
 model_type: sdar
+pipeline_tag: text-generation
+library_name: transformers
 ---
 <h1 align="center">DiRL-8B-Instruct</h1>