Columbia-NLP/gemma-2b-zephyr-sft

Columbia-NLP/gemma-2b-zephyr-sft is a 2.5 billion parameter GPT-like model, fine-tuned by Columbia-NLP from Google's Gemma-2b using the deita-10k-v0-sft dataset. It is primarily English-language and optimized for supervised fine-tuning performance through careful hyper-parameter selection and user token masking. This model demonstrates improved performance across various benchmarks, including a 48.75 average on the OpenLLM Leaderboard and a 4.34 total on MT-Bench, making it suitable for general conversational AI tasks where a smaller, efficient model with strong SFT performance is desired.