
EasyInstruct is an easy-to-use instruction processing framework for Large Language Models (LLMs), facilitating instruction generation, selection, and prompting to enhance data quality and diversity.


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easyinstruct-an-instruction-processing-framework-for-large-language-models


EasyInstruct: An Instruction Processing Framework for Large Language Models


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モジュール式の機械翻訳システムの効率的なトレーニングとスケーリングに焦点を当てたMAMMOTHツールキットが紹介されました。


mammoth-modular-multilingual-translation-toolkit-for-efficient-nlp


MAMMOTH: Modular Multilingual Translation Toolkit for Efficient NLP



RWKV model combines RNN efficiency with Transformer scale, addressing key limitations in NLP.


How an RNN Style Architecture is challenging the dominance of Transformers in NLP

RWKV: The cheaper and better future of NLP and LLMs?

unveiling-rwkv-weaknesses-innovations-and-impact-on-nlp


Unveiling RWKV: Weaknesses, Innovations, and Impact on NLP



The authors investigate the performance of transformer language models on embedded devices, focusing on resource constraints and accuracy requirements. They explore trade-offs between model size, accuracy, and system resources.


analyzing-transformer-models-for-natural-language-processing-on-embedded-devices


Analyzing Transformer Models for Natural Language Processing on Embedded Devices
