# ProphetNet
## Overview The ProphetNet model was proposed in [ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training,](https://arxiv.org/abs/2001.04063) by Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang, Ming Zhou on 13 Jan, 2020. ProphetNet is an encoder-decoder model and can predict n-future tokens for "ngram" language modeling instead of just the next token. The abstract from the paper is the following: *In this paper, we present a new sequence-to-sequence pretraining model called ProphetNet, which introduces a novel self-supervised objective named future n-gram prediction and the proposed n-stream self-attention mechanism. Instead of the optimization of one-step ahead prediction in traditional sequence-to-sequence model, the ProphetNet is optimized by n-step ahead prediction which predicts the next n tokens simultaneously based on previous context tokens at each time step. The future n-gram prediction explicitly encourages the model to plan for the future tokens and prevent overfitting on strong local correlations. We pre-train ProphetNet using a base scale dataset (16GB) and a large scale dataset (160GB) respectively. Then we conduct experiments on CNN/DailyMail, Gigaword, and SQuAD 1.1 benchmarks for abstractive summarization and question generation tasks. Experimental results show that ProphetNet achieves new state-of-the-art results on all these datasets compared to the models using the same scale pretraining corpus.* The Authors' code can be found [here](https://github.com/microsoft/ProphetNet). ## Usage tips - ProphetNet is a model with absolute position embeddings so it's usually advised to pad the inputs on the right rather than the left. - The model architecture is based on the original Transformer, but replaces the “standard” self-attention mechanism in the decoder by a main self-attention mechanism and a self and n-stream (predict) self-attention mechanism. ## Resources - [Causal language modeling task guide](../tasks/language_modeling) - [Translation task guide](../tasks/translation) - [Summarization task guide](../tasks/summarization) ## ProphetNetConfig [[autodoc]] ProphetNetConfig ## ProphetNetTokenizer [[autodoc]] ProphetNetTokenizer ## ProphetNet specific outputs [[autodoc]] models.prophetnet.modeling_prophetnet.ProphetNetSeq2SeqLMOutput [[autodoc]] models.prophetnet.modeling_prophetnet.ProphetNetSeq2SeqModelOutput [[autodoc]] models.prophetnet.modeling_prophetnet.ProphetNetDecoderModelOutput [[autodoc]] models.prophetnet.modeling_prophetnet.ProphetNetDecoderLMOutput ## ProphetNetModel [[autodoc]] ProphetNetModel - forward ## ProphetNetEncoder [[autodoc]] ProphetNetEncoder - forward ## ProphetNetDecoder [[autodoc]] ProphetNetDecoder - forward ## ProphetNetForConditionalGeneration [[autodoc]] ProphetNetForConditionalGeneration - forward ## ProphetNetForCausalLM [[autodoc]] ProphetNetForCausalLM - forward