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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README.md
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<a href="https://x.com/dmind_ai" target="_blank" style="margin: 2px;">
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<img alt="X" src="https://img.shields.io/badge/X-@DMind-1DA1F2?logo=x" style="display: inline-block; vertical-align: middle;"/>
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</a>
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<a href="https://
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<img alt="Chat" src="https://img.shields.io/badge/🤖%20Chat-DMind--1--mini-536af5?color=536af5&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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</a>
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<a href="https://discord.gg/xxwmPHU3" target="_blank" style="margin: 2px;">
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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.
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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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**API Endpoint:**
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```
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https://openrouter.ai/api/v1/chat/completions
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```
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**Authentication:**
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- Obtain your API key from [OpenRouter](https://openrouter.ai/)
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- Include it in the `Authorization` header as `Bearer YOUR_API_KEY`
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**Model Identifiers:**
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- `DMind-1-mini` — Full-size expert model
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**Example Request (Python):**
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```python
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import requests
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headers = {
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"Authorization": "Bearer YOUR_API_KEY",
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"Content-Type": "application/json"
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}
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data = {
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"model": "DMind-1-mini",
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"messages": [
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{"role": "user", "content": "Explain DeFi in simple terms."}
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]
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}
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response = requests.post(
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"https://openrouter.ai/api/v1/chat/completions",
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headers=headers,
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json=data
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print(response.json())
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```
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**Example Request (cURL):**
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curl https://openrouter.ai/api/v1/chat/completions \
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-H "Authorization: Bearer YOUR_API_KEY" \
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-H "Content-Type: application/json" \
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-d '{
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"model": "DMind-1-mini",
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"messages": [{"role": "user", "content": "What is a smart contract?"}]
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}'
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```
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**Notes:**
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- Replace `YOUR_API_KEY` with your actual OpenRouter API key.
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- Change the `model` field to `DMind-1-mini` as needed.
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- Both models support the same API structure for easy integration.
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### 4.3 OpenRouter Web Chat
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You can try **DMind-1-mini** instantly using the [OpenRouter Web Chat](https://openrouter.ai/chat).
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- Select your desired model from the dropdown menu (**DMind-1-mini**).
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- Enter your prompt and interact with the model in real time.
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[](https://openrouter.ai/chat)
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## License
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- The code repository and model weights for DMind-1-mini is released under the MIT License.
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<a href="https://x.com/dmind_ai" target="_blank" style="margin: 2px;">
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<img alt="X" src="https://img.shields.io/badge/X-@DMind-1DA1F2?logo=x" style="display: inline-block; vertical-align: middle;"/>
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</a>
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<a href="https://huggingface.co/spaces/DMindAI/DMind-1-mini" target="_blank" style="margin: 2px;">
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<img alt="Chat" src="https://img.shields.io/badge/🤖%20Chat-DMind--1--mini-536af5?color=536af5&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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</a>
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<a href="https://discord.gg/xxwmPHU3" target="_blank" style="margin: 2px;">
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|:--------------:|:--------------:|:----------------------------------------------------------------------------:|
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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 (Coming Soon)
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*Documentation for API access will be available soon.*
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### 4.3 OpenRouter Web Chat (Coming Soon)
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*Web chat interface documentation will be available soon.*
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## License
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- The code repository and model weights for DMind-1-mini is released under the MIT License.
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