added prompt file

Summary: Pull Request resolved: https://github.com/pytorch/fairseq/pull/1385

Differential Revision: D18565188

Pulled By: huihuifan

fbshipit-source-id: 9580663b208f286a249bbfa2bacd71f34a01ca9f

examples/stories/README.md

@@ -8,7 +8,7 @@ Description | Dataset | Model | Test set(s)
 ---|---|---|---
 Stories with Convolutional Model <br> ([Fan et al., 2018](https://arxiv.org/abs/1805.04833)) | [WritingPrompts](https://arxiv.org/abs/1805.04833) | [download (.tar.bz2)](https://dl.fbaipublicfiles.com/fairseq/models/stories_checkpoint.tar.bz2) | [download (.tar.bz2)](https://dl.fbaipublicfiles.com/fairseq/data/stories_test.tar.bz2)
 
-We provide sample stories generated by the [convolutional seq2seq model](https://dl.fbaipublicfiles.com/fairseq/data/seq2seq_stories.txt) and [fusion model](https://dl.fbaipublicfiles.com/fairseq/data/fusion_stories.txt) from [Fan et al., 2018](https://arxiv.org/abs/1805.04833).
+We provide sample stories generated by the [convolutional seq2seq model](https://dl.fbaipublicfiles.com/fairseq/data/seq2seq_stories.txt) and [fusion model](https://dl.fbaipublicfiles.com/fairseq/data/fusion_stories.txt) from [Fan et al., 2018](https://arxiv.org/abs/1805.04833). The corresponding prompts for the fusion model can be found [here](https://dl.fbaipublicfiles.com/fairseq/data/fusion_prompts.txt). Note that there are unk in the file, as we modeled a small full vocabulary (no BPE or pre-training). We did not use these unk prompts for human evaluation.
 
 ## Dataset