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cs.CL2024★ 2 cited
INDUS: Effective and Efficient Language Models for Scientific Applications
Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka +33
Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs tr…
cs.CL2024
Accelerating Production LLMs with Combined Token/Embedding Speculators
Davis Wertheimer, Joshua Rosenkranz, Thomas Parnell +4
This technical report describes the design and training of novel speculative decoding draft models, for accelerating the inference speeds of large language models in a production e…