Just an extra note, that is the key point why EuclidesDB support multiple models, so you can have for instance a ResNet trained on ImageNet for some images and

Just an extra note, that is the key point why EuclidesDB support multiple models, so you can have for instance a ResNet trained on ImageNet for some images and another ResNet (same architecture) fine-tuned on your data (domain adapted) for another different semantic space. A concrete example is to think in the example of a fashion company who has fine-tuned different models for different product categories: Model A = fine-tuned to classify between different types of shoes; Model B = fine-tuned to classify between different t-shirt types; EuclidesDB can have these two models and you can add/query items into each one of these different models (hence the concept of "model/module space" that is used by EuclidesDB).