From 008c2d0b7aecfa53116346ffd8f8c51d38c59140 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aleksander=20Smywi=C5=84ski-Pohl?= Date: Thu, 9 Sep 2021 14:00:05 +0200 Subject: [PATCH] Fix typo in documentation (#13494) * Fix typo in deepspeed documentation * Add missing import in deepspeed configuration * Fix path in translation examples --- examples/pytorch/translation/README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/examples/pytorch/translation/README.md b/examples/pytorch/translation/README.md index 2af7fb335b..1eca845961 100644 --- a/examples/pytorch/translation/README.md +++ b/examples/pytorch/translation/README.md @@ -42,7 +42,7 @@ and you also will find examples of these below. Here is an example of a translation fine-tuning with a MarianMT model: ```bash -python examples/pytorch/seq2seq/run_translation.py \ +python examples/pytorch/translation/run_translation.py \ --model_name_or_path Helsinki-NLP/opus-mt-en-ro \ --do_train \ --do_eval \ @@ -62,7 +62,7 @@ MBart and some T5 models require special handling. T5 models `t5-small`, `t5-base`, `t5-large`, `t5-3b` and `t5-11b` must use an additional argument: `--source_prefix "translate {source_lang} to {target_lang}"`. For example: ```bash -python examples/pytorch/seq2seq/run_translation.py \ +python examples/pytorch/translation/run_translation.py \ --model_name_or_path t5-small \ --do_train \ --do_eval \ @@ -85,7 +85,7 @@ For the aforementioned group of T5 models it's important to remember that if you MBart models require a different format for `--source_lang` and `--target_lang` values, e.g. instead of `en` it expects `en_XX`, for `ro` it expects `ro_RO`. The full MBart specification for language codes can be found [here](https://huggingface.co/facebook/mbart-large-cc25). For example: ```bash -python examples/pytorch/seq2seq/run_translation.py \ +python examples/pytorch/translation/run_translation.py \ --model_name_or_path facebook/mbart-large-en-ro \ --do_train \ --do_eval \ @@ -104,7 +104,7 @@ And here is how you would use the translation finetuning on your own files, afte values for the arguments `--train_file`, `--validation_file` to match your setup: ```bash -python examples/pytorch/seq2seq/run_translation.py \ +python examples/pytorch/translation/run_translation.py \ --model_name_or_path t5-small \ --do_train \ --do_eval \ @@ -133,7 +133,7 @@ Here the languages are Romanian (`ro`) and English (`en`). If you want to use a pre-processed dataset that leads to high BLEU scores, but for the `en-de` language pair, you can use `--dataset_name stas/wmt14-en-de-pre-processed`, as following: ```bash -python examples/pytorch/seq2seq/run_translation.py \ +python examples/pytorch/translation/run_translation.py \ --model_name_or_path t5-small \ --do_train \ --do_eval \