LLMOps: Fine-Tuning Video Classifier (ViViT) with Custom Data

LLMOps: Fine-Tuning Video Classifier (ViViT) with Custom Data

Learn how to fine-tune a Video Vision Transformer (ViViT) using your own dataset in this comprehensive 44-minute tutorial. Explore the process of leveraging a pretrained model by Google (google/vivit-b-16x2-kinetics400), initially trained on the Kinetics-400 dataset, and adapt it to classify videos from a different dataset. Gain hands-on experience in implementing LLMOps techniques for machine learning and data science applications. Access the accompanying code repository on GitHub to follow along and enhance your skills in video classification using state-of-the-art transformer models.