🧠 DQN Labs

DQN Labs is an independent AI research project focused on building, training, and experimenting with Large Language Models (LLMs).

Our goal is to push the limits of small, efficient AI models and make powerful AI systems accessible to everyone.

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🔬 Current Focus

DQN Labs is currently focused on LLM development and fine-tuning, including:

• 🧠 Training and fine-tuning open-source language models
• 💻 Improving code generation and reasoning ability
• 📊 Evaluating models on benchmarks such as HumanEval
• ⚡ Running efficient experiments on consumer hardware

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📦 What You'll Find Here

This organization hosts:

• 🤖 Fine-tuned language models
• 📚 Training datasets
• 🧪 Experimental checkpoints
• 📊 Evaluation results and benchmarks

Most experiments focus on efficient training methods and lightweight models.

Everybody is free to contribute to the organizations, whether you choose to do so through providing new data, sharing your research through papers, or even fine tuning a few models yoruself!

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🛠 Tech Stack

• Python
• PyTorch
• Hugging Face Transformers
• MLX (Apple Silicon optimization)
• LoRA / parameter-efficient fine-tuning

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🎯 Vision

DQN Labs is exploring how capable small AI models can become through better data, smarter training, and efficient infrastructure.

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🌐 Links

• 🤗 Hugging Face: DQN Labs (you're here already!)
• 🎥 YouTube: DQN Labs

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⚡ Motto

Local AI for everyone.