| {"paper_url": "https://huggingface.co/papers/2309.11197", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Frustratingly Simple Memory Efficiency for Pre-trained Language Models via Dynamic Embedding Pruning](https://huggingface.co/papers/2309.08708) (2023)\n* [Do Generative Large Language Models need billions of parameters?](https://huggingface.co/papers/2309.06589) (2023)\n* [XGen-7B Technical Report](https://huggingface.co/papers/2309.03450) (2023)\n* [Qwen Technical Report](https://huggingface.co/papers/2309.16609) (2023)\n* [RecycleGPT: An Autoregressive Language Model with Recyclable Module](https://huggingface.co/papers/2308.03421) (2023)\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space"} |