Expand description
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 aspiece.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
- MBART model configuration
- MBART Pretrained model config files
- MBart Model for conditional generation
- MBart Model for sequence classification
- Language generation model based on the MBart architecture
- MBart Base model
- MBART Pretrained model weight files
- MBART source languages pre-sets
- MBART Pretrained model vocab files
Type Aliases
- Container holding a MBART model output
- MBART target languages pre-sets