From b0b9b8091b73f929306704bd8cd62b712621cebc Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Tue, 20 Aug 2019 11:33:46 +0200 Subject: [PATCH] minor typo --- pytorch_transformers/modeling_gpt2.py | 2 +- pytorch_transformers/modeling_openai.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pytorch_transformers/modeling_gpt2.py b/pytorch_transformers/modeling_gpt2.py index f67d0e88d5..dd3e465bf3 100644 --- a/pytorch_transformers/modeling_gpt2.py +++ b/pytorch_transformers/modeling_gpt2.py @@ -614,7 +614,7 @@ class GPT2LMHeadModel(GPT2PreTrainedModel): @add_start_docstrings("""The GPT2 Model transformer with a language modeling and a multiple-choice classification head on top e.g. for RocStories/SWAG tasks. The two heads are two linear layers. The language modeling head has its weights tied to the input embeddings, -the classification head takes as input the input of a specified classification token index in the intput sequence). +the classification head takes as input the input of a specified classification token index in the input sequence). """, GPT2_START_DOCSTRING) class GPT2DoubleHeadsModel(GPT2PreTrainedModel): r""" Inputs: diff --git a/pytorch_transformers/modeling_openai.py b/pytorch_transformers/modeling_openai.py index e8648487be..a4f02111e7 100644 --- a/pytorch_transformers/modeling_openai.py +++ b/pytorch_transformers/modeling_openai.py @@ -604,7 +604,7 @@ class OpenAIGPTLMHeadModel(OpenAIGPTPreTrainedModel): @add_start_docstrings("""OpenAI GPT Model transformer with a language modeling and a multiple-choice classification head on top e.g. for RocStories/SWAG tasks. The two heads are two linear layers. The language modeling head has its weights tied to the input embeddings, -the classification head takes as input the input of a specified classification token index in the intput sequence). +the classification head takes as input the input of a specified classification token index in the input sequence). """, OPENAI_GPT_START_DOCSTRING) class OpenAIGPTDoubleHeadsModel(OpenAIGPTPreTrainedModel): r""" Inputs: