This is gemma-2b model supervised fine-tuned on the vicgalle/alpaca-gpt4 dataset. It outperforms gemma-2b-it, Google's chat version, on Nous' benchmark suite.

It's mostly a test to see how fine-tuning works with Gemma models on a well-known dataset. It turned out better than expected. :)

This model has a context length of 8k. I recommend using it with the Alpaca chat template and NOT the Gemma Instruct template (works perfectly with LM Studio). You also want to add </s> as a stop token.

Gemmalpaca-2B outperforms gemma-2b and gemma-2b-it on Nous' benchmark suite (evaluation performed using LLM AutoEval). See the entire leaderboard here.

It was trained using Axolotl with the following configuration.