Instructions to use DMindAI/DMind-1-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DMindAI/DMind-1-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DMindAI/DMind-1-mini") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DMindAI/DMind-1-mini", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use DMindAI/DMind-1-mini with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DMindAI/DMind-1-mini" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DMindAI/DMind-1-mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/DMindAI/DMind-1-mini
- SGLang
How to use DMindAI/DMind-1-mini 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-1-mini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DMindAI/DMind-1-mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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-1-mini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DMindAI/DMind-1-mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use DMindAI/DMind-1-mini with Docker Model Runner:
docker model run hf.co/DMindAI/DMind-1-mini
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| DMind-1-mini | Qwen3-14B | [Hugging Face Link](https://huggingface.co/dmind-ai/dmind-1-mini) |
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### 4.2 OpenRouter API
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You can access **DMind-1-mini** via the OpenRouter API. Simply specify the desired model in the `model` field of your request payload.
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| DMind-1-mini | Qwen3-14B | [Hugging Face Link](https://huggingface.co/dmind-ai/dmind-1-mini) |
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**System Prompt (recommended):**
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For optimal performance, we recommend using the following system prompt while using the DMind models:
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```
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You are DMind AI Assistant, built by DMind.AI.
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Focus — Web3 depth: DeFi, NFT, MEME, DePIN, RWA; real-time market & trading insights.
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Identity rules:
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- Never present as Qwen, ChatGPT, Tongyi, OpenAI, etc.
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- If asked: "I'm DMind AI Assistant, developed by DMind.AI."
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```
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### 4.2 OpenRouter API
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You can access **DMind-1-mini** via the OpenRouter API. Simply specify the desired model in the `model` field of your request payload.
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