Module pegasus

Pegasus (Zhang et al.)

Implementation of the Pegasus language model (PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization Zhang, Zhao, Saleh, Liu, 2019). The base model is implemented in the pegasus_model::PegasusModel struct and leverages an implementation that is broadly similar to BART. The model also includes a language model head: pegasus_model::PegasusForConditionalGeneration 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

A full working example is provided in examples/summarization_pegasus, run with cargo run --example summarization_pegasus. 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.
• PegasusTokenizer using a spiece.model vocabulary and unigram model.

Pretrained models are available and can be downloaded using RemoteResources.

use tch::{nn, Device};
use rust_bert::pegasus::{PegasusConfig, PegasusModel};
use rust_bert::resources::{LocalResource, ResourceProvider};
use rust_bert::Config;
use rust_tokenizers::tokenizer::PegasusTokenizer;

let config_resource = LocalResource {
    local_path: PathBuf::from("path/to/config.json"),
};
let vocab_resource = LocalResource {
    local_path: PathBuf::from("path/to/spiece.model"),
};
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: PegasusTokenizer =
    PegasusTokenizer::from_file(vocab_path.to_str().unwrap(), false)?;
let config = PegasusConfig::from_file(config_path);
let pegasus_model = PegasusModel::new(&vs.root(), &config);
vs.load(weights_path)?;

Structs

PegasusConditionalGenerator

Language generation model based on the Pegasus architecture

PegasusConfigResources

Pegasus Pretrained model config files

PegasusForConditionalGeneration

Pegasus Model for conditional generation

PegasusModel

Pegasus Base model

PegasusModelResources

Pegasus Pretrained model weight files

PegasusVocabResources

Pegasus Pretrained model vocab files

Type Aliases

LayerState

Cache for Pegasus attention layers

PegasusConfig

Pegasus model configuration