Buckets:
generation/parameters
- generation/parameters
~GenerationFunctionParametersBase: Object~GenerationFunctionParameters: GenerationFunctionParametersBase | Partial.<GenerationConfig>
generation/parameters~GenerationFunctionParametersBase : Object
Kind: inner typedef of generation/parameters
Properties
NameTypeDefaultDescription
[inputs]Tensor(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(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(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]StoppingCriteria | Array | StoppingCriteriaList(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(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 | Tensor(number[] or Tensor, optional):
If the model is an encoder-decoder model, this argument is used to pass the decoder_input_ids.
[past_key_values]DynamicCache | null(DynamicCache, optional):
A cache object that stores previously computed key/value states. When provided, the model will use these cached states to avoid recomputing them, significantly speeding up sequential generation.
generation/parameters~GenerationFunctionParameters : GenerationFunctionParametersBase | Partial.<GenerationConfig>
Kind: inner typedef of generation/parameters
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