Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Large models represent a groundbreaking advancement in multiple application fields,
enabling remarkable achievements across various tasks. However, their unprecedented …

We present QLoRA, an efficient finetuning approach that reduces memory usage enough to
finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit …

Large language models (LLMs) have revolutionized the field of artificial intelligence,
enabling natural language processing tasks that were previously thought to be exclusive to …

Ever since the Turing Test was proposed in the 1950s, humans have explored the mastering
of language intelligence by machine. Language is essentially a complex, intricate system of …

Large language models (LLMs) have shown remarkable capabilities in language
understanding and generation. However, such impressive capability typically comes with a …

We introduce the Falcon series: 7B, 40B, and 180B parameters causal decoder-only models
trained on a diverse high-quality corpora predominantly assembled from web data. The …

As their size increases, Large Languages Models (LLMs) are natural candidates for network
pruning methods: approaches that drop a subset of network weights while striving to …

Abstract Large Language Models (LLMs), despite their recent impressive accomplishments,
are notably cost-prohibitive to deploy, particularly for applications involving long-content …

We introduce the Yi model family, a series of language and multimodal models that
demonstrate strong multi-dimensional capabilities. The Yi model family is based on 6B and …