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. :)
🔍 Applications
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
.
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