Instructions to use nvidia/Nemotron-Labs-Audex-30B-A3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/Nemotron-Labs-Audex-30B-A3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nvidia/Nemotron-Labs-Audex-30B-A3B")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/Nemotron-Labs-Audex-30B-A3B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nvidia/Nemotron-Labs-Audex-30B-A3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nvidia/Nemotron-Labs-Audex-30B-A3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nvidia/Nemotron-Labs-Audex-30B-A3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nvidia/Nemotron-Labs-Audex-30B-A3B
- SGLang
How to use nvidia/Nemotron-Labs-Audex-30B-A3B 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/Nemotron-Labs-Audex-30B-A3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nvidia/Nemotron-Labs-Audex-30B-A3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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/Nemotron-Labs-Audex-30B-A3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nvidia/Nemotron-Labs-Audex-30B-A3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nvidia/Nemotron-Labs-Audex-30B-A3B with Docker Model Runner:
docker model run hf.co/nvidia/Nemotron-Labs-Audex-30B-A3B
Demo for this model on Spaces
Hey @L0SG and NVIDIA folks 🤗, it's me again, Poli from Hugging Face
You keep shipping 🚢 — congrats on nvidia/Nemotron-Labs-Audex-30B-A3B! Once again, me + my agent built an interactive demo app of it on Hugging Face Spaces, running on a free ZeroGPU infrastructure.
Here's a link to the demo: https://huggingface.co/spaces/hugging-apps/nvidia-nemotron-labs-audex-30b-a3b
And you know the spiel, but it would be great to transfer it to your organization/user on Hugging Face. Just let me know which username/org to transfer over, we hope it can give your work more visibility, discoverability and allows folks to try it out.
In the future, feel free to already ship models with demos included. You can use this one as a blueprint to build by yourself or with the help of an agent — you can load the huggingface-spaces skill on Claude Code, Codex, Pi, etc.
(If you have any questions or just want to chat more about this, you can find me on Twitter, LinkedIn or apolinario @ huggingface.co)
Cheers,
Poli
Hi @multimodalart , thank you very much for providing a space demo. I can iterate on polishing; would be great if this can transferred to my account first (@L0SG ) before we add it to the collection (https://huggingface.co/collections/nvidia/nemotron-labs-audex).
Thanks,
Sanggil
Awesome @L0SG ! I've transferred the model to your personal account, feel free to iterate and when ready to add to the NVIDIA one 🤗
https://huggingface.co/spaces/L0SG/nemotron-labs-audex-30b-a3b