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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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/** * Helper function to create multiple InferenceSession objects. * * @param {string} pretrained_model_name_or_path The path to the directory containing the model file. * @param {Record<string, string>} names The names of the model files to load. * @param {import('../utils/hub.js').PretrainedModelOptions} options Additional options for loading the model. * @param {Record<string, true>} [cache_sessions] A map from session name to `true`, indicating which * sessions should have GPU-pinned KV cache outputs. * @returns {Promise<Record<string, any>>} A Promise that resolves to a dictionary of InferenceSession objects. * @private */ export function constructSessions(pretrained_model_name_or_path: string, names: Record<string, string>, options: import("../utils/hub.js").PretrainedModelOptions, cache_sessions?: Record<string, true>): Promise<Record<string, any>>; /** * Executes an InferenceSession using the specified inputs. * NOTE: `inputs` must contain at least the input names of the model. * - If additional inputs are passed, they will be ignored. * - If inputs are missing, an error will be thrown. * * @param {Object} session The InferenceSession object to run. * @param {Object} inputs An object that maps input names to input tensors. * @returns {Promise<Object>} A Promise that resolves to an object that maps output names to output tensors. * @private */ export function sessionRun(session: any, inputs: any): Promise<any>; //# sourceMappingURL=session.d.ts.map