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package=ai.vespa.example.paragraph
# WordPiece tokenizer vocabulary
vocab model
model model
myValue string
# Max length of token sequence model can handle
transforerMaxTokens int default=128
# Pooling strategy
poolingStrategy enum { cls, mean } default=mean
# Input names
transformerInputIds string default=input_ids
transformerAttentionMask string default=attention_mask
# Output name
transformerOutput string default=last_hidden_state
# Settings for ONNX model evaluation
onnxExecutionMode enum { parallel, sequential } default=sequential
onnxInterOpThreads int default=1
onnxIntraOpThreads int default=-4
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