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Model: neulab/gpt2-finetuned-wikitext103
Source: Original Platform

README.md

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+This is a `gpt2` model, finetuned on the Wikitext-103 dataset.
+
+It achieves a perplexity of **14.84** using a "sliding window" context, using the `run_clm.py` script at [https://github.com/neulab/knn-transformers](https://github.com/neulab/knn-transformers).
+
+| Base LM:        | `distilgpt2` | `gpt2` | 
+| :---            |    ----:   |     ---: |
+| base perplexity | 18.25      | 14.84    |
+| +kNN-LM          |  15.03     |   12.57  |
+| +RetoMaton       | **14.70**  |  **12.46**    |
+
+This model was released as part of the paper ["Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval"](https://arxiv.org/pdf/2201.12431.pdf) (ICML'2022).
+
+For more information, see: [https://github.com/neulab/knn-transformers](https://github.com/neulab/knn-transformers)
+
+If you use this model, please cite:
+```
+@inproceedings{alon2022neuro,
+  title={Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval},
+  author={Alon, Uri and Xu, Frank and He, Junxian and Sengupta, Sudipta and Roth, Dan and Neubig, Graham},
+  booktitle={International Conference on Machine Learning},
+  pages={468--485},
+  year={2022},
+  organization={PMLR}
+}
+```