

Zero-shot VQA
The previous model treated VQA as a classification task. Some recent models, such as BLIP, BLIP-2, and InstructBLIP approach 
VQA as a generative task. Let's take BLIP-2 as an example. It introduced a new visual-language pre-training 
paradigm in which any combination of pre-trained vision encoder and LLM can be used (learn more in the BLIP-2 blog post). 
This enables achieving state-of-the-art results on multiple visual-language tasks including visual question answering. 
Let's illustrate how you can use this model for VQA. First, let's load the model. Here we'll explicitly send the model to a 
GPU, if available, which we didn't need to do earlier when training, as [Trainer] handles this automatically: 