I am a currently studying multimodal deep learning, and I would like to implement a model that can process both images and text. I am looking for a code example $($preferably in Python using frameworks like PyTorch$)$ that demonstrates how to train a model that takes both an image and a text input simultaneously.

Could you please provide a step$-$by$-$step guide or a tutorial that explains the key components, such as:

How to preprocess and feed images and text into the model.

How to design the architecture of a multimodal model $($e$.$g$.,$ combining CNN for images and LTSM$/$Transformer for text$).$

How to merge features from both modalities for the final prediction task.

Any common challenges or pitfalls when training multimodal models, and how to address them.

Thank you!