📄️ Connect to SuperDuperDB
Note that this is only relevant if you are running SuperDuperDB in development mode.
📄️ Create datatype
Data types such as "text" or "integer" which are natively support by your db.databackend don't need a datatype.
📄️ Get useful sample data
📄️ Insert data
In order to create data, we need to create a Schema for encoding our special Datatype column(s) in the databackend.
📄️ Compute features
📄️ Build text embedding model
📄️ Build image embedding model
Construct a neural network architecture to project high-dimensional image data into a lower-dimensional, dense vector representation
📄️ Build multimodal embedding models
Some embedding models such as CLIP come in pairs of model and compatible_model.
📄️ Build LLM
📄️ Create vector-index
📄️ Perform a vector search
Once we have this search target, we can execute a search as follows:
📄️ Connecting listeners
📄️ Build and train classifier
The following command adds the model to the system and trains the model in one command.