llmsresearch/scone
Implementation and evaluation of Scaling Embedding Layers in Language Models research paper
This project helps machine learning engineers improve the performance of large language models while keeping inference costs in check. It allows you to train models that process text more effectively by using a novel embedding approach for frequent word sequences. The output is a more accurate and efficient language model, ideal for those working with extensive text datasets.
Use this if you are developing or fine-tuning large language models and need to enhance their performance and memory efficiency without increasing inference-time computational load.
Not ideal if you are looking for a plug-and-play solution for basic text processing or if you do not have experience with training and deploying machine learning models.
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13
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2
Language
Python
License
MIT
Category
Last pushed
Feb 02, 2026
Commits (30d)
0
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