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+ This is a `gpt2-med` model, finetuned on the Wikitext-103 dataset.
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+ It achieves a perplexity of **11.55** using a "sliding window" context, using the `run_clm.py` script at [https://github.com/neulab/knn-transformers](https://github.com/neulab/knn-transformers).
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+ | Base LM: | `distilgpt2` | `gpt2` |
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+ | :--- | ----: | ---: |
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+ | base perplexity | 18.25 | 14.84 |
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+ | + kNN-LM | 15.03 | 12.57 |
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+ | + RetoMaton | **14.70** | **12.46** |
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+ 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).
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+ For more information, see: [https://github.com/neulab/knn-transformers](https://github.com/neulab/knn-transformers)