Fine-tuning Gemma-2–2B-it for Translation

This guide demonstrates how to fine-tune a Gemma 2 2B model for English to Hindi translation using large language models (LLMs). LLMs leverage vast datasets and advanced architectures, such as transformers, to accurately capture the nuances of different languages. Multilingual tokenization significantly enhances a model's ability to perform accurate translations by recognizing and handling different scripts, vocabulary, and grammar structures. MonsterAPI's LLM fine-tuning engine simplifies this process, allowing users to pick a model and perform instruction fine-tuning for translation tasks.