BertModel

ruvector_sparse_inference::model::runners

Struct BertModel 

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pub struct BertModel {
    pub metadata: ModelMetadata,
    pub embeddings: BertEmbeddings,
    pub encoder: Vec<BertLayer>,
    pub pooler: Option<Pooler>,
}

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§metadata: ModelMetadata§embeddings: BertEmbeddings§encoder: Vec<BertLayer>§pooler: Option<Pooler>

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impl ModelRunner for BertModel

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fn forward( &self, input: &ModelInput, config: &InferenceConfig, ) -> Result<ModelOutput, SparseInferenceError>

Forward pass with optional sparse computation
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fn get_predictor(&self, _layer_idx: usize) -> Option<&LowRankPredictor>

Get predictor for a specific layer (if available)
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fn calibrate( &mut self, _samples: &[ModelInput], ) -> Result<CalibrationStats, SparseInferenceError>

Calibrate predictors with sample data
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fn metadata(&self) -> &ModelMetadata

Get model metadata

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