Instructions to use OpenGVLab/SDLM-3B-D8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OpenGVLab/SDLM-3B-D8 with Transformers:

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

pipe = pipeline("text-generation", model="OpenGVLab/SDLM-3B-D8", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("OpenGVLab/SDLM-3B-D8", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("OpenGVLab/SDLM-3B-D8", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use OpenGVLab/SDLM-3B-D8 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OpenGVLab/SDLM-3B-D8"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OpenGVLab/SDLM-3B-D8",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/OpenGVLab/SDLM-3B-D8

SGLang

How to use OpenGVLab/SDLM-3B-D8 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 "OpenGVLab/SDLM-3B-D8" \
    --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": "OpenGVLab/SDLM-3B-D8",
		"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 "OpenGVLab/SDLM-3B-D8" \
        --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": "OpenGVLab/SDLM-3B-D8",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use OpenGVLab/SDLM-3B-D8 with Docker Model Runner:
```
docker model run hf.co/OpenGVLab/SDLM-3B-D8
```

Add project page link to model card

by nielsr HF Staff - opened Oct 1, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+15

-15

nielsr

Oct 1, 2025

This PR enhances the model card by adding a link to the project page (https://internvl.github.io/blog/2025-09-29-SDLM/) in the introductory section. This improves discoverability for users seeking additional context and information about the project.

The existing metadata and content (including the paper link to arXiv and the sample usage) remain unchanged as they are already accurate and meet the documentation guidelines.

Add project page link to model card305dff10

lll2343 changed pull request status to merged Oct 3, 2025

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