export interface ConversionConfig { inputPath: string; outputPath: string; inputFormat: 'pytorch' | 'tensorflow' | 'onnx' | 'gguf' | 'tflite' | 'safetensors'; outputFormat: 'pytorch' | 'tensorflow' | 'onnx' | 'gguf' | 'tflite' | 'safetensors'; modelType?: string; quantization?: QuantizationConfig; pruning?: PruningConfig; graphOptimization?: GraphOptimizationConfig; validation?: boolean; } export interface QuantizationConfig { method: 'int8' | 'int16' | 'fp16' | 'dynamic' | 'static'; calibrationData?: string; targetDevice?: 'cpu' | 'gpu' | 'mobile'; } export interface PruningConfig { method: 'magnitude' | 'structured' | 'unstructured'; sparsity: number; targetLayers?: string[]; } export interface GraphOptimizationConfig { fuseOperations: boolean; removeUnusedNodes: boolean; optimizeMemory: boolean; } export declare class ModelConverter { private converters; initialize(): Promise<{ success: boolean; message: string; }>; convert(config: ConversionConfig): Promise<{ success: boolean; message: string; outputPath: string; model: any; }>; private applyQuantization; private applyPruning; private applyGraphOptimization; validateModel(modelPath: string, format: string): Promise; getModelInfo(modelPath: string, format: string): Promise; batchConvert(configs: ConversionConfig[]): Promise<{ success: boolean; message: string; outputPath: string; model: any; }[]>; } export declare function pytorchToONNX(inputPath: string, outputPath: string, config?: Partial): Promise<{ success: boolean; message: string; outputPath: string; model: any; }>; export declare function tensorflowToTFLite(inputPath: string, outputPath: string, config?: Partial): Promise<{ success: boolean; message: string; outputPath: string; model: any; }>; export declare function pytorchToGGUF(inputPath: string, outputPath: string, config?: Partial): Promise<{ success: boolean; message: string; outputPath: string; model: any; }>; //# sourceMappingURL=modelConversion.d.ts.map