Fine Tuneing Google’s Gemma

Led the fine-tuning of Google’s GEMMA for natural language understanding, improving model accuracy by 15%.Utilized TensorFlow and Hugging Face Transformers for model optimization and deployment.
Reduced training time by 25% through efficient data preprocessing and augmentation techniques.Collaborated with data scientists and software engineers to integrate the model into production, enhancing the system’s overall performance.