Instructions to use nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16 with Transformers:

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

pipe = pipeline("text-generation", model="nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16", 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 nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16

SGLang

How to use nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16 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 "nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16" \
    --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": "nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16",
		"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 "nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16" \
        --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": "nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16 with Docker Model Runner:
```
docker model run hf.co/nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16
```

jrd971000 commited on May 7

Commit

0eb43bd

1 Parent(s): 08ae39d

Add Nemotron Labs Elastic logo to top of model card

Browse files

Files changed (3) hide show

.gitattributes +1 -0
README.md +4 -0
star_elastic_logo.png +3 -0

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@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md CHANGED Viewed

@@ -21,6 +21,10 @@ license: other
 # NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16
 <div align="center" style="line-height: 1;">
 <a href="https://arxiv.org/abs/2511.16664" target="_blank" style="margin: 2px;">
     <img alt="Paper" src="https://img.shields.io/badge/📝Paper-Read Now!-536af5?color=76B900&logoColor=white" style="display: inline-block; vertical-align: middle;"/>

 # NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16
+<div align="center">
+  <img src="./star_elastic_logo.png" alt="Nemotron Labs Elastic" width="500"/>
+</div>
 <div align="center" style="line-height: 1;">
 <a href="https://arxiv.org/abs/2511.16664" target="_blank" style="margin: 2px;">
     <img alt="Paper" src="https://img.shields.io/badge/📝Paper-Read Now!-536af5?color=76B900&logoColor=white" style="display: inline-block; vertical-align: middle;"/>

star_elastic_logo.png ADDED Viewed

Git LFS Details

SHA256: c32b4f4c958391b426647229194dce17719dbdb0ff01e060686064c603f1787c
Pointer size: 132 Bytes
Size of remote file: 2.5 MB