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@huggingface/transformers

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State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!

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import { IMAGE_PROCESSOR_NAME } from '../constants.js'; import { get_file_metadata } from './get_file_metadata.js'; /** * Returns the list of processor files that will be loaded for a model. * Auto-detects if the model has a processor by checking if preprocessor_config.json exists. * * @param {string} modelId The model id (e.g., "Xenova/detr-resnet-50") * @returns {Promise<string[]>} Array of processor file names (empty if no processor) */ export async function get_processor_files(modelId) { if (!modelId) { throw new Error('modelId is required'); } // Check if preprocessor_config.json exists const metadata = await get_file_metadata(modelId, IMAGE_PROCESSOR_NAME, {}); return metadata.exists ? [IMAGE_PROCESSOR_NAME] : []; }