private void validateModel() {
        Map<String, TensorType> inputs = evaluator.getInputInfo();
        validateName(inputs, inputIdsName, "input");
        validateName(inputs, attentionMaskName, "input");
        Map<String, TensorType> outputs = evaluator.getOutputInfo();
        validateName(outputs, outputName, "output");
    }
A ColBERT embedder implementation that maps text to multiple vectors, one vector per token subword id.
This embedder uses a HuggingFace tokenizer to produce a token sequence that is then input to a transformer model.

See col-bert-embedder.def for configurable parameters.

@author bergum
model-integration/src/main/java/ai/vespa/embedding/ColBertEmbedder.java