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
- 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
Update model/config.json
Browse files- model/config.json +16 -5
model/config.json
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"attn_logit_softcapping": null,
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"bos_token_id": 2,
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"dtype": "bfloat16",
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"eos_token_id":
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"final_logit_softcapping": null,
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"head_dim": 256,
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"hidden_activation": "gelu_pytorch_tanh",
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"pad_token_id": 0,
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"query_pre_attn_scalar": 256,
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"rms_norm_eps": 1e-06,
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"sliding_window": 512,
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"use_bidirectional_attention": false,
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"use_cache": true,
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"vocab_size": 262144
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"attn_logit_softcapping": null,
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"bos_token_id": 2,
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"dtype": "bfloat16",
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"eos_token_id": [
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],
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"final_logit_softcapping": null,
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"head_dim": 256,
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"hidden_activation": "gelu_pytorch_tanh",
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"pad_token_id": 0,
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"query_pre_attn_scalar": 256,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"full_attention": {
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"rope_theta": 1000000.0,
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"rope_type": "default"
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},
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"sliding_attention": {
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"rope_theta": 10000.0,
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"rope_type": "default"
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}
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},
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"sliding_window": 512,
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"tie_word_embeddings": true,
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"transformers_version": "5.2.0",
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"use_bidirectional_attention": false,
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"use_cache": true,
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"vocab_size": 262144
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