Struct rust_bert::pipelines::generation_utils::GenerateConfig [−][src]
pub struct GenerateConfig {Show 19 fields
pub model_resource: Resource,
pub config_resource: Resource,
pub vocab_resource: Resource,
pub merges_resource: Resource,
pub min_length: i64,
pub max_length: i64,
pub do_sample: bool,
pub early_stopping: bool,
pub num_beams: i64,
pub temperature: f64,
pub top_k: i64,
pub top_p: f64,
pub repetition_penalty: f64,
pub length_penalty: f64,
pub no_repeat_ngram_size: i64,
pub num_return_sequences: i64,
pub num_beam_groups: Option<i64>,
pub diversity_penalty: Option<f64>,
pub device: Device,
}
Expand description
Fields
model_resource: Resource
Model weights resource (default: pretrained GPT2 model)
config_resource: Resource
Config resource (default: pretrained GPT2 model)
vocab_resource: Resource
Vocab resource (default: pretrained GPT2 model)
merges_resource: Resource
Merges resource (default: pretrained GPT2 model)
min_length: i64
Minimum sequence length (default: 0)
max_length: i64
Maximum sequence length (default: 20)
do_sample: bool
Sampling flag. If true, will perform top-k and/or nucleus sampling on generated tokens, otherwise greedy (deterministic) decoding (default: true)
early_stopping: bool
Early stopping flag indicating if the beam search should stop as soon as num_beam
hypotheses have been generated (default: false)
num_beams: i64
Number of beams for beam search (default: 5)
temperature: f64
Temperature setting. Values higher than 1 will improve originality at the risk of reducing relevance (default: 1.0)
top_k: i64
Top_k values for sampling tokens. Value higher than 0 will enable the feature (default: 0)
top_p: f64
Top_p value for Nucleus sampling, Holtzman et al.. Keep top tokens until cumulative probability reaches top_p (default: 0.9)
repetition_penalty: f64
Repetition penalty (mostly useful for CTRL decoders). Values higher than 1 will penalize tokens that have been already generated. (default: 1.0)
length_penalty: f64
Exponential penalty based on the length of the hypotheses generated (default: 1.0)
no_repeat_ngram_size: i64
Number of allowed repetitions of n-grams. Values higher than 0 turn on this feature (default: 3)
num_return_sequences: i64
Number of sequences to return for each prompt text (default: 1)
num_beam_groups: Option<i64>
Number of beam groups for diverse beam generation. If provided and higher than 1, will split the beams into beam subgroups leading to more diverse generation.
diversity_penalty: Option<f64>
Diversity penalty for diverse beam search. High values will enforce more difference between beam groups (default: 5.5)
device: Device
Device to place the model on (default: CUDA/GPU when available)
Trait Implementations
Returns the “default value” for a type. Read more
Performs the conversion.
Performs the conversion.
Performs the conversion.
Performs the conversion.
Auto Trait Implementations
impl RefUnwindSafe for GenerateConfig
impl Send for GenerateConfig
impl Sync for GenerateConfig
impl Unpin for GenerateConfig
impl UnwindSafe for GenerateConfig
Blanket Implementations
Mutably borrows from an owned value. Read more
Instruments this type with the provided Span
, returning an
Instrumented
wrapper. Read more
type Output = T
type Output = T
Should always be Self