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Merge pull request #815 from praateekmahajan/update-readme-link 

Update Readme link for Fine Tune/Usage section
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Thomas Wolf 2019-07-18 18:30:32 +02:00 committed by GitHub
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@ -19,7 +19,7 @@ These implementations have been tested on several datasets (see the example scri
|-|-|
| [Installation](#installation) | How to install the package |
| [Quick tour: Usage](#quick-tour-usage) | Tokenizers & models usage: Bert and GPT-2 |
| [Quick tour: Fine-tuning/usage scripts](#quick-tour-fine-tuningusage-scripts) | Using provided scripts: GLUE, SQuAD and Text generation |
| [Quick tour: Fine-tuning/usage scripts](#quick-tour-of-the-fine-tuningusage-scripts) | Using provided scripts: GLUE, SQuAD and Text generation |
| [Migrating from pytorch-pretrained-bert to pytorch-transformers](#Migrating-from-pytorch-pretrained-bert-to-pytorch-transformers) | Migrating your code from pytorch-pretrained-bert to pytorch-transformers |
| [Documentation](https://huggingface.co/pytorch-transformers/) | Full API documentation and more |
@ -118,7 +118,6 @@ tokenizer = tokenizer_class.from_pretrained(pretrained_weights)
```
## Quick tour of the fine-tuning/usage scripts
The library comprises several example scripts with SOTA performances for NLU and NLG tasks:
- `run_glue.py`: an example fine-tuning Bert, XLNet and XLM on nine different GLUE tasks (*sequence-level classification*)