Module mbart

MBart (Liu et al.)

Implementation of the MBart language model (Multilingual Denoising Pre-training for Neural Machine Translation Liu, Gu, Goyal, Li, Edunov, Ghazvininejad, Lewis, Zettlemoyer, 2020). The base model is implemented in the mbart_model::MBartModel struct. The model also includes a language model head: mbart_model::MBartForConditionalGeneration implementing the common generation_utils::LanguageGenerator trait shared between the models used for generation (see pipelines for more information).

Model set-up and pre-trained weights loading

The translation capabilities are illustrated in examples/translation_mbart, run with cargo run --example translation_mbart. All models expect the following resources:

• Configuration file expected to have a structure following the Transformers library
• Model weights are expected to have a structure and parameter names following the Transformers library. A conversion using the Python utility scripts is required to convert the .bin weights to the .ot format.
• MBart50Tokenizer using a spiece.model SentencePiece model

Pretrained models are available and can be downloaded using RemoteResources.

use tch::{nn, Device};
use rust_bert::mbart::{MBartConfig, MBartModel};
use rust_bert::resources::{LocalResource, ResourceProvider};
use rust_bert::Config;
use rust_tokenizers::tokenizer::MBart50Tokenizer;

let config_resource = LocalResource {
    local_path: PathBuf::from("path/to/config.json"),
};
let vocab_resource = LocalResource {
    local_path: PathBuf::from("path/to/vocab.txt"),
};
let weights_resource = LocalResource {
    local_path: PathBuf::from("path/to/model.ot"),
};
let config_path = config_resource.get_local_path()?;
let vocab_path = vocab_resource.get_local_path()?;
let weights_path = weights_resource.get_local_path()?;

let device = Device::cuda_if_available();
let mut vs = nn::VarStore::new(device);
let tokenizer: MBart50Tokenizer =
    MBart50Tokenizer::from_file(vocab_path.to_str().unwrap(), false)?;
let config = MBartConfig::from_file(config_path);
let mbart_model = MBartModel::new(&vs.root(), &config);
vs.load(weights_path)?;

Structs

MBartConfig

MBART model configuration

MBartConfigResources

MBART Pretrained model config files

MBartForConditionalGeneration

MBart Model for conditional generation

MBartForSequenceClassification

MBart Model for sequence classification

MBartGenerator

Language generation model based on the MBart architecture

MBartModel

MBart Base model

MBartModelResources

MBART Pretrained model weight files

MBartSourceLanguages

MBART source languages pre-sets

MBartVocabResources

MBART Pretrained model vocab files

Type Aliases

LayerState

MBartModelOutput

Container holding a MBART model output

MBartTargetLanguages

MBART target languages pre-sets