Text Generation
Transformers
Safetensors
English
Chinese
function-calling
tool-use
crypto
blockchain
solana
ethereum
on-device
privacy
edge-ai
mobile
wallet
standard-protocol
Instructions to use DMindAI/DMind-3-nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DMindAI/DMind-3-nano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DMindAI/DMind-3-nano")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DMindAI/DMind-3-nano", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use DMindAI/DMind-3-nano with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DMindAI/DMind-3-nano" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DMindAI/DMind-3-nano", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DMindAI/DMind-3-nano
- SGLang
How to use DMindAI/DMind-3-nano 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 "DMindAI/DMind-3-nano" \ --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": "DMindAI/DMind-3-nano", "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 "DMindAI/DMind-3-nano" \ --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": "DMindAI/DMind-3-nano", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DMindAI/DMind-3-nano with Docker Model Runner:
docker model run hf.co/DMindAI/DMind-3-nano
Download .gitignore from DMindAI/DMind-3-nano: direct link, hf CLI and curl.
- Browser
- Download file 416 Bytes
-
https://huggingface.co/DMindAI/DMind-3-nano/resolve/main/.gitignore
- Command line
-
hf download hf://DMindAI/DMind-3-nano/.gitignore
-
curl -L -o .gitignore https://huggingface.co/DMindAI/DMind-3-nano/resolve/main/.gitignore
416 Bytes
| # macOS | |
| .DS_Store | |
| **/.DS_Store | |
| # Python | |
| __pycache__/ | |
| *.py[cod] | |
| *$py.class | |
| *.so | |
| .Python | |
| build/ | |
| develop-eggs/ | |
| dist/ | |
| downloads/ | |
| eggs/ | |
| .eggs/ | |
| lib/ | |
| lib64/ | |
| parts/ | |
| sdist/ | |
| var/ | |
| wheels/ | |
| *.egg-info/ | |
| .installed.cfg | |
| *.egg | |
| # Virtual Environment | |
| venv/ | |
| ENV/ | |
| env/ | |
| # IDE | |
| .vscode/ | |
| .idea/ | |
| *.swp | |
| *.swo | |
| *~ | |
| # Data artifacts (generated files) | |
| data/prepared_dataset.json | |
| # Upload scripts (optional, kept for convenience) | |
| # upload_*.py | |