transformers.js/pr_1472/en/api/generation/parameters.md

generation/parameters

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generation/parameters~GenerationFunctionParameters : Object

Kind: inner typedef of generation/parameters

  ParamTypeDescription




[kwargs]any(Dict[str, any], optional):

  

Properties

  NameTypeDefaultDescription




[inputs]*(Tensor of varying shape depending on the modality, optional):

The sequence used as a prompt for the generation or as model inputs to the encoder. If null the method initializes it with bos_token_id and a batch size of 1. For decoder-only models inputs should be in the format of input_ids. For encoder-decoder models inputs can represent any of input_ids, input_values, input_features, or pixel_values.

[generation_config]*(GenerationConfig, optional):

The generation configuration to be used as base parametrization for the generation call. **kwargs passed to generate matching the attributes of generation_config will override them. If generation_config is not provided, the default will be used, which has the following loading priority:

(1) from the generation_config.json model file, if it exists; (2) from the model configuration. Please note that unspecified parameters will inherit [GenerationConfig]'s default values, whose documentation should be checked to parameterize generation.

[logits_processor]*(LogitsProcessorList, optional):

Custom logits processors that complement the default logits processors built from arguments and generation config. If a logit processor is passed that is already created with the arguments or a generation config an error is thrown. This feature is intended for advanced users.

[stopping_criteria]*(StoppingCriteriaList, optional):

Custom stopping criteria that complements the default stopping criteria built from arguments and a generation config. If a stopping criteria is passed that is already created with the arguments or a generation config an error is thrown. This feature is intended for advanced users.

[streamer]*(BaseStreamer, optional):

Streamer object that will be used to stream the generated sequences. Generated tokens are passed through streamer.put(token_ids) and the streamer is responsible for any further processing.

[decoder_input_ids]Array.<number>(number[], optional):

If the model is an encoder-decoder model, this argument is used to pass the decoder_input_ids.

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