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examples/README.md
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In this section a few examples are put together. All of these examples work for several models, making use of the very
similar API between the different models.
| Section | Description |
|----------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [Language Model fine-tuning](#language-model-fine-tuning) | Fine-tuning the library models for language modeling on a text dataset. Causal language modeling for GPT/GPT-2, masked language modeling for BERT/RoBERTa. |
| [Language Generation](#language-generation) | Conditional text generation using the auto-regressive models of the library: GPT, GPT-2, Transformer-XL and XLNet. |
| [GLUE](#glue) | Examples running BERT/XLM/XLNet/RoBERTa on the 9 GLUE tasks. Examples feature distributed training as well as half-precision. |
| [SQuAD](#squad) | Using BERT for question answering, examples with distributed training. |
## Language model fine-tuning
Based on the script `run_lm_finetuning.py`.