@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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TypeScript
export * from "./pipelines.js";
export * from "./models/models.js";
export * from "./models/auto/modeling_auto.js";
export * from "./models/tokenizers.js";
export * from "./models/auto/tokenization_auto.js";
export * from "./models/feature_extractors.js";
export * from "./models/auto/feature_extraction_auto.js";
export * from "./models/image_processors.js";
export * from "./models/auto/image_processing_auto.js";
export * from "./models/processors.js";
export * from "./models/auto/processing_auto.js";
export * from "./generation/streamers.js";
export * from "./generation/stopping_criteria.js";
export * from "./generation/logits_process.js";
export * from "./utils/tensor.js";
export { random } from "./utils/random.js";
export { DynamicCache } from "./cache_utils.js";
export { ModelRegistry } from "./utils/model_registry/ModelRegistry.js";
export type PretrainedModelOptions = import("./utils/hub.js").PretrainedModelOptions;
export type PretrainedProcessorOptions = import("./processing_utils.js").PretrainedProcessorOptions;
export type Message = import("./tokenization_utils.js").Message;
export type PretrainedTokenizerOptions = import("./tokenization_utils.js").PretrainedTokenizerOptions;
export type DataType = import("./utils/dtypes.js").DataType;
export type DeviceType = import("./utils/devices.js").DeviceType;
export type ProgressCallback = import("./utils/core.js").ProgressCallback;
export type ProgressInfo = import("./utils/core.js").ProgressInfo;
export { env, LogLevel } from "./env.js";
export { PretrainedConfig, AutoConfig } from "./configs.js";
export { load_audio, read_audio, RawAudio } from "./utils/audio.js";
export { load_image, RawImage } from "./utils/image.js";
export { load_video, RawVideo, RawVideoFrame } from "./utils/video.js";
export { softmax, log_softmax, dot, cos_sim } from "./utils/maths.js";
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