🤖 Model Details

• Base Architecture: Qwen2
• Parameter Count: ~600M
• Languages: Korean, English

💻 Hardware & Compute

• Hardware: Trained on Kaggle Notebooks using 2x NVIDIA T4 GPUs (16GB VRAM each).
• Constraints: Navigating the memory constraints of a 600M parameter model on 16GB GPUs without advanced quantization required aggressive gradient accumulation and small batch sizes, leading to the decision to pivot to the highly efficient ~135M architecture for Bori-2 to allow for more robust pre-training experimentation.

⚠️ Limitations & Intended Use

This model was paused very early in its training lifecycle. It is significantly undertrained and exhibits poor coherence. It should not be used for text generation, fine-tuning, or deployment. Its primary value is as a historical artifact demonstrating the early stages of the Bori project's development.