/**
 * BitNet 1-bit Quantized Classifier for Resource Types
 *
 * A small, purpose-built neural network using 1-bit weight quantization.
 * Classifies cloud resource type strings into verification categories.
 *
 * Architecture:
 * - Tokenizer: splits resource types on underscores
 * - Embedding: maps tokens to vectors
 * - 1-bit Linear layers: weights in {-1, 0, +1}
 * - Output: 13 category logits
 */
import type { VerificationCategory } from './categories.js';
import { type TrainingExample } from './training-data.js';
/**
 * BitNet classifier model
 */
export interface BitNetModel {
    vocabulary: Map<string, number>;
    embeddings: number[][];
    hiddenWeights: number[][];
    hiddenBias: number[];
    outputWeights: number[][];
    outputBias: number[];
    config: {
        embedDim: number;
        hiddenDim: number;
        maxTokens: number;
    };
}
/**
 * Train the BitNet model
 */
export declare function trainBitNet(data: TrainingExample[], config: {
    embedDim: number;
    hiddenDim: number;
    maxTokens: number;
    epochs: number;
    learningRate: number;
}): BitNetModel;
/**
 * Evaluate model accuracy
 */
export declare function evaluateBitNet(model: BitNetModel, data: TrainingExample[]): {
    accuracy: number;
    perCategory: Record<string, {
        correct: number;
        total: number;
    }>;
};
/**
 * Classify a resource type using the trained model
 */
export declare function classifyWithBitNet(model: BitNetModel, resourceType: string): {
    category: VerificationCategory;
    confidence: number;
    allScores: Record<string, number>;
};
/**
 * Serialize model to JSON (for shipping with package)
 */
export declare function serializeModel(model: BitNetModel): string;
/**
 * Deserialize model from JSON
 */
export declare function deserializeModel(json: string): BitNetModel;
/**
 * Train and export a model using the built-in training data
 */
export declare function trainDefaultModel(): BitNetModel;
/**
 * Get the pre-trained model (lazy load)
 */
export declare function getPretrainedModel(): BitNetModel;
/**
 * Load pre-trained weights if available
 */
export declare function loadPretrainedWeights(json: string): void;
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