Instructions to use nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16" # 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-TwoTower-30B-A3B-Base-BF16", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16
- SGLang
How to use nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-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/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16" \ --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-TwoTower-30B-A3B-Base-BF16", "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-TwoTower-30B-A3B-Base-BF16" \ --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-TwoTower-30B-A3B-Base-BF16", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16 with Docker Model Runner:
docker model run hf.co/nvidia/Nemotron-Labs-TwoTower-30B-A3B-Base-BF16
Fix _mdlm_forward: unmasked positions get all-zero probabilities (scatter into a discarded copy)
#4 opened 1 day ago
by
pierrelamy
Request: DOI
#3 opened 4 days ago
by
torouni
torch_forward CPU path crashes: cache .device/.zero_() called on list instead of per-layer tensor
#2 opened 7 days ago
by
AutomatedJanitor
Question about the architecture and checkpoint size of the Two-Tower Model
👍 1
#1 opened 9 days ago
by
lssj14