Phi-3 technical report: A highly capable language model locally on your phone
M Abdin, J Aneja, H Awadalla, A Awadallah… - ar** Large Language Models (LLMs) with up to trillion
parameters has been met with concerns regarding resource efficiency and practical …
parameters has been met with concerns regarding resource efficiency and practical …
Tinygpt-v: Efficient multimodal large language model via small backbones
In recent years, multimodal large language models (MLLMs) such as GPT-4V have
demonstrated remarkable advancements, excelling in a variety of vision-language tasks …
demonstrated remarkable advancements, excelling in a variety of vision-language tasks …
Smaller, weaker, yet better: Training llm reasoners via compute-optimal sampling
Training on high-quality synthetic data from strong language models (LMs) is a common
strategy to improve the reasoning performance of LMs. In this work, we revisit whether this …
strategy to improve the reasoning performance of LMs. In this work, we revisit whether this …
Tinyllava: A framework of small-scale large multimodal models
We present the TinyLLaVA framework that provides a unified perspective in designing and
analyzing the small-scale Large Multimodal Models (LMMs). We empirically study the effects …
analyzing the small-scale Large Multimodal Models (LMMs). We empirically study the effects …