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# FineInfer | ||
<h1 align="center"> | ||
FineInfer | ||
</h1> | ||
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<p align="center"> | ||
| <a href="https://dl.acm.org/doi/10.1145/3642970.3655835"><b>Paper</b></a> | | ||
</p> | ||
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FineInfer is a research prototype for fine-tuning and serving large language models. | ||
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FineInfer supports concurrent parameter-efficient fine-tuning and inference through the following features: | ||
* Deferred continuous batching | ||
* Hybrid system architecture | ||
* Heterogeneous batching | ||
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## Installation and examples | ||
[See here](https://github.com/llm-db/FineInfer/blob/main/benchmarks/fineinfer/README.md) | ||
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## Citation | ||
``` | ||
@inproceedings{FineInfer, | ||
author = {He, Yongjun and Lu, Yao and Alonso, Gustavo}, | ||
title = {Deferred Continuous Batching in Resource-Efficient Large Language Model Serving}, | ||
year = {2024}, | ||
booktitle = {Proceedings of the 4th Workshop on Machine Learning and Systems}, | ||
pages = {98–106}, | ||
series = {EuroMLSys '24} | ||
} | ||
``` |
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