Now how do I combine these two models?
The simplest approach is to average the predictions. If it is a regression model, or model returns some kind of scores, you can simply average them between models. Additionally, for combining probabilities you have multiple options. If it returns classifications, then with more then two models you can use majority voting.
Is this a valid approach given the two models use different parts of
the training data?
It is not only valid, but in many cases you could expect that this should improve the overall accuracy of the predictions. Combining different models is a popular approach, especially in machine learning competitions on sites like Kaggle. Usually you get better results if you combine models that differ from each other, then when using very similar models.
On another hand, in cases like yours, people often use models that use all the data, e.g. neural network that has a module for tabular data and another module for textual data, where the modules are combined at some point, to calculate final prediction.