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

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

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
OpenAiGptModel	GPT Base model