Instructions to use DQN-Labs/dqnGPT-v0.1-3.8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use DQN-Labs/dqnGPT-v0.1-3.8B with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M # Run inference directly in the terminal: llama cli -hf DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M # Run inference directly in the terminal: llama cli -hf DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M
Use Docker
docker model run hf.co/DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use DQN-Labs/dqnGPT-v0.1-3.8B with Ollama:
ollama run hf.co/DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use DQN-Labs/dqnGPT-v0.1-3.8B with Docker Model Runner:
docker model run hf.co/DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M
- Lemonade
How to use DQN-Labs/dqnGPT-v0.1-3.8B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DQN-Labs/dqnGPT-v0.1-3.8B:Q4_K_M
Run and chat with the model
lemonade run user.dqnGPT-v0.1-3.8B-Q4_K_M
List all available models
lemonade list
- Atomic Chat
π§ DQN GPT v0.1
Local AI for Everyone.
DQN GPT v0.1 is a lightweight, locally runnable assistant built on Phi-3 Mini (3.8B parameters).
This release is an early identity-alignment version focused on establishing personality and behavioral consistency. It is not yet a domain-specialized or heavily fine-tuned model.
This is the foundation.
π Vision
Local AI for everyone.
DQN GPT exists to prove that powerful AI does not need to live in a datacenter.
It should run:
- On laptops
- On student machines
- On modest hardware
- On personal servers
- On local networks
AI should be accessible.
π§ Base Model
- Architecture: Phi-3 Mini
- Parameter Count: 3.8B
- Context Length: 128K (as supported by base model)
- Format: GGUF (llama.cpp / LM Studio compatible)
π§ Fine-Tuning Details
This version has been fine-tuned on a minimal identity-alignment dataset for testing purposes.
Focus areas:
- Assistant identity consistency
- Stable conversational tone
- Reduced drift from defined persona
This is not a performance-focused or coding-specialized release yet.
Future updates will include:
- Coding-focused fine-tuning
- Hallucination reduction
- Improved reasoning
- Broader conversational robustness
π» Hardware Requirements
Designed to run locally.
Recommended:
- 8GB+ RAM (Q4_K_M quant)
- CPU inference supported
- GPU optional
Quantization options determine performance and memory usage.
π¦ Intended Use
- Local assistant
- Personal AI experimentation
- LAN-hosted AI servers
- Offline productivity
- Student AI access
β Limitations
- Early-stage release
- Minimal dataset fine-tune
- Not benchmark-optimized
- Not trained for specialized domains yet
This is v0.1 β a foundation build.
π£ Roadmap
- Coding-specialized variant
- Refined conversational dataset
- Larger releases
- Improved reliability
- Public evaluation benchmarks
π Philosophy
AI should not be locked behind subscriptions.
AI should not require a supercomputer.
AI should run where you are.
Local AI for everyone.
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Model tree for DQN-Labs/dqnGPT-v0.1-3.8B
Base model
microsoft/Phi-3-mini-4k-instruct