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")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DMindAI/DMind-3-nano", dtype="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
| { | |
| "backend": "tokenizers", | |
| "boi_token": "<start_of_image>", | |
| "bos_token": "<bos>", | |
| "clean_up_tokenization_spaces": false, | |
| "eoi_token": "<end_of_image>", | |
| "eos_token": "<eos>", | |
| "image_token": "<image_soft_token>", | |
| "is_local": true, | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "model_specific_special_tokens": { | |
| "boi_token": "<start_of_image>", | |
| "eoi_token": "<end_of_image>", | |
| "image_token": "<image_soft_token>", | |
| "sfr_token": "<start_function_response>" | |
| }, | |
| "pad_token": "<pad>", | |
| "padding_side": "left", | |
| "sfr_token": "<start_function_response>", | |
| "sp_model_kwargs": null, | |
| "spaces_between_special_tokens": false, | |
| "tokenizer_class": "GemmaTokenizer", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } | |