From d3046dad809b7b10019b142ae20b49fb58d21c28 Mon Sep 17 00:00:00 2001 From: Stefan Schweter Date: Wed, 8 Feb 2023 15:39:52 +0100 Subject: [PATCH] [Doc] Minor URL fixes in PyTorch Text Classification Readme (#21511) docs: fix some references in PyTorch text classification readme --- examples/pytorch/text-classification/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/pytorch/text-classification/README.md b/examples/pytorch/text-classification/README.md index 391aaf4d3f0..1bc01b416b7 100644 --- a/examples/pytorch/text-classification/README.md +++ b/examples/pytorch/text-classification/README.md @@ -173,9 +173,9 @@ Note that this library is in alpha release so your feedback is more than welcome ## XNLI -Based on the script [`run_xnli.py`](https://github.com/huggingface/transformers/examples/pytorch/text-classification/run_xnli.py). +Based on the script [`run_xnli.py`](https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_xnli.py). -[XNLI](https://www.nyu.edu/projects/bowman/xnli/) is a crowd-sourced dataset based on [MultiNLI](http://www.nyu.edu/projects/bowman/multinli/). It is an evaluation benchmark for cross-lingual text representations. Pairs of text are labeled with textual entailment annotations for 15 different languages (including both high-resource language such as English and low-resource languages such as Swahili). +[XNLI](https://cims.nyu.edu/~sbowman/xnli/) is a crowd-sourced dataset based on [MultiNLI](https://cims.nyu.edu/~sbowman/multinli/). It is an evaluation benchmark for cross-lingual text representations. Pairs of text are labeled with textual entailment annotations for 15 different languages (including both high-resource language such as English and low-resource languages such as Swahili). #### Fine-tuning on XNLI