Outperforming SOTA LLMs for Less than the Cost of a Coffee with Monster Tuner

MonsterAPI has successfully fine-tuned the Mistral 7B language model using their no-code LLM finetuner, resulting in superior performance compared to state-of-the-art models like Falcon and Zephyr. The finetuned Mistral model demonstrated an average score of 47.04, outperforming the Falcon models with scores around 38. Additionally, the fine-tuned Zephyr model excelled in TruthfulQA. MonsterAPI's no-code LLM finetuner simplifies the complex process of fine-tuning language models and reduces costs, making it easier for developers to harness their power.