Buckets:
processors
Processors are used to prepare inputs (e.g., text, image or audio) for a model.
Example: Using a WhisperProcessor to prepare an audio input for a model.
import { AutoProcessor, read_audio } from '@huggingface/transformers';
const processor = await AutoProcessor.from_pretrained('openai/whisper-tiny.en');
const audio = await read_audio('https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/mlk.flac', 16000);
const { input_features } = await processor(audio);
// Tensor {
// data: Float32Array(240000) [0.4752984642982483, 0.5597258806228638, 0.56434166431427, ...],
// dims: [1, 80, 3000],
// type: 'float32',
// size: 240000,
// }
- processors
- static
- .Processor
new Processor(config, components, chat_template)- instance
.image_processor⇒ ImageProcessor | undefined.tokenizer⇒ PreTrainedTokenizer | undefined.feature_extractor⇒ FeatureExtractor | undefined.apply_chat_template(messages, options)⇒ ReturnType.<PreTrainedTokenizer>.batch_decode(...args)⇒ ReturnType.<PreTrainedTokenizer>.decode(...args)⇒ ReturnType.<PreTrainedTokenizer>._call(input, ...args)⇒ Promise.<any>
- static
.from_pretrained(pretrained_model_name_or_path, options)⇒ Promise.<Processor>
- .Processor
- inner
~PreTrainedTokenizer: Object
- static
processors.Processor
Represents a Processor that extracts features from an input.
Kind: static class of processors
- .Processor
new Processor(config, components, chat_template)- instance
.image_processor⇒ ImageProcessor | undefined.tokenizer⇒ PreTrainedTokenizer | undefined.feature_extractor⇒ FeatureExtractor | undefined.apply_chat_template(messages, options)⇒ ReturnType.<PreTrainedTokenizer>.batch_decode(...args)⇒ ReturnType.<PreTrainedTokenizer>.decode(...args)⇒ ReturnType.<PreTrainedTokenizer>._call(input, ...args)⇒ Promise.<any>
- static
.from_pretrained(pretrained_model_name_or_path, options)⇒ Promise.<Processor>
new Processor(config, components, chat_template)
Creates a new Processor with the given components
ParamType
configObject
componentsRecord.<string, Object>
chat_templatestring
processor.image_processor ⇒ ImageProcessor | undefined
Kind: instance property of Processor
Returns: ImageProcessor | undefined - The image processor of the processor, if it exists.
processor.tokenizer ⇒ PreTrainedTokenizer | undefined
Kind: instance property of Processor
Returns: PreTrainedTokenizer | undefined - The tokenizer of the processor, if it exists.
processor.feature_extractor ⇒ FeatureExtractor | undefined
Kind: instance property of Processor
Returns: FeatureExtractor | undefined - The feature extractor of the processor, if it exists.
processor.apply_chat_template(messages, options) ⇒ ReturnType.<PreTrainedTokenizer>
Kind: instance method of Processor
ParamType
messagesParameters
optionsParameters
processor.batch_decode(...args) ⇒ ReturnType.<PreTrainedTokenizer>
Kind: instance method of Processor
ParamType
...argsParameters.<PreTrainedTokenizer>
processor.decode(...args) ⇒ ReturnType.<PreTrainedTokenizer>
Kind: instance method of Processor
ParamType
...argsParameters.<PreTrainedTokenizer>
processor._call(input, ...args) ⇒ Promise.<any>
Calls the feature_extractor function with the given input.
Kind: instance method of Processor
Returns: Promise.<any> - A Promise that resolves with the extracted features.
ParamTypeDescription
inputanyThe input to extract features from.
...argsanyAdditional arguments.
Processor.from_pretrained(pretrained_model_name_or_path, options) ⇒ Promise.<Processor>
Instantiate one of the processor classes of the library from a pretrained model.
The processor class to instantiate is selected based on the image_processor_type (or feature_extractor_type; legacy)
property of the config object (either passed as an argument or loaded from pretrained_model_name_or_path if possible)
Kind: static method of Processor
Returns: Promise.<Processor> - A new instance of the Processor class.
ParamTypeDescription
pretrained_model_name_or_pathstringThe name or path of the pretrained model. Can be either:
A string, the model id of a pretrained processor hosted inside a model repo on huggingface.co. Valid model ids can be located at the root-level, like bert-base-uncased, or namespaced under a user or organization name, like dbmdz/bert-base-german-cased. A path to a directory containing processor files, e.g., ./my_model_directory/.
optionsPretrainedProcessorOptionsAdditional options for loading the processor.
processors~PreTrainedTokenizer : Object
Additional processor-specific properties.
Kind: inner typedef of processors
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