Struct rust_bert::pipelines::generation::MarianGenerator

pub struct MarianGenerator { /* fields omitted */ }

Language generation model based on the Marian architecture for machine translation

Implementations

impl MarianGenerator

pub fn new(generate_config: GenerateConfig) -> Fallible<MarianGenerator>

Build a new marianGenerator

Arguments

• vocab_path - Path to the model vocabulary, expected to have a structure following the Transformers library convention
• sentencepiece_model_path - Path to the sentencepiece model (native protobuf expected)
• config_path - Path to the model configuration, expected to have a structure following the Transformers library convention
• weights_path - Path to the model weight files. These need to be converted form the .bin to .ot format using the utility script provided.
• device - Device to run the model on, e.g. Device::Cpu or Device::Cuda(0)

Example

use rust_bert::pipelines::generation::{GenerateConfig, MarianGenerator};
let device = Device::cuda_if_available();
let generate_config = GenerateConfig {
    max_length: 512,
    do_sample: true,
    num_beams: 6,
    temperature: 1.0,
    num_return_sequences: 1,
    ..Default::default()
};
let marian_generator = MarianGenerator::new(generate_config)?;

Trait Implementations

impl LanguageGenerator<MarianForConditionalGeneration, MarianVocab, MarianTokenizer> for MarianGenerator

fn generate(
    &self,
    prompt_texts: Option<Vec<&str>>,
    attention_mask: Option<Tensor>
) -> Vec<String>

Generate text based on a vector of promp texts.

fn generate_from_ids_and_past(
    &self,
    input_ids: Tensor,
    attention_mask: Option<Tensor>
) -> Vec<Vec<i64>>