Module rust_bert::openai_gpt

GPT (Radford et al.)

Implementation of the GPT2 language model (Improving Language Understanding by Generative Pre-Training Radford, Narasimhan, Salimans, Sutskever 2018). The base model is implemented in the openai_gpt::OpenAiGptModel struct. The model also includes a language model head: openai_gpt::OpenAIGPTLMHeadModel implementing the common generation::LMHeadModel 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/openai_gpt.rs, run with cargo run --example openai_gpt. 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.
• GptTokenizer using a vocab.txt vocabulary and merges.txt 2-gram merges Pretrained models are available and can be downloaded using RemoteResources.

use rust_tokenizers::OpenAiGptTokenizer;
use tch::{nn, Device};
use rust_bert::gpt2::Gpt2Config;
use rust_bert::openai_gpt::OpenAiGptModel;
use rust_bert::resources::{download_resource, LocalResource, Resource};
use rust_bert::Config;

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

let device = Device::cuda_if_available();
let mut vs = nn::VarStore::new(device);
let tokenizer: OpenAiGptTokenizer = OpenAiGptTokenizer::from_file(
    vocab_path.to_str().unwrap(),
    merges_path.to_str().unwrap(),
    true,
);
let config = Gpt2Config::from_file(config_path);
let gpt_model = OpenAiGptModel::new(&vs.root(), &config);
vs.load(weights_path)?;

Structs

OpenAIGPTLMHeadModel	GPT Language Modeling head
OpenAiGptConfigResources	GPT Pretrained model config files
OpenAiGptMergesResources	GPT Pretrained model merges files
OpenAiGptModel	GPT Base model
OpenAiGptModelResources	GPT Pretrained model weight files
OpenAiGptVocabResources	GPT Pretrained model vocab files