Large language models (LLMs) have recently enjoyed much success, e.g.,achieving 50% accuracyon high school math competition questions. These models can solve various tasks using the right prompts or fine-tuning, such as translation, summarization, or question answering. One path to human-level ...
Recent large language models (LLMs), such as ChatGPT, have demonstrated remarkable prediction performance for a growing array of tasks. However, their proliferation into high-stakes domains and compute-limited settings has created a burgeoning need for interpretability and efficiency. We address this ...
Logical reasoning of text is an important ability that requires understanding the 1 logical information present in the text and reasoning through them to infer new 2 conclusions. Prior works on improving the logical reasoning ability of language 3 models require complex processing of training data (...
14、Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models(DeepMindpaper) Google Deepmind提出的Step Back prompt方法,显著提升了推理数据的准确性。这种提示技术,首先让llm做抽象,以派生高级概念和第一原则,然后使用概念和原则来指导推理,显著提高了模型正确推理的能力。实验表明,模型在各种具...
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. 在一天内为生物医学领域训练一个大型语言和视觉助手。 题目更想表达的是训练速度快。LLaVA-Med是使用8个A100在不到15小时的时间内训练完成。A100显存是40G,8个A100不是普通组能有的配置。 2.2 动机 通用领域的多模态LLM...
DeepSpeed-MoE for NLG: Reducing the training cost of language models by five times While recent works like GShard (opens in new tab) and Switch Transformers (opens in new tab) have shown that the MoE model structure can reduce large model pretraining cost for encoder-de...
An open platform for training, serving, and evaluating large language model for tool learning. openbmb.github.io/ToolBench/ Resources Readme License Apache-2.0 license Activity Custom properties Stars 0 stars Watchers 0 watching Forks 0 forks Report repository Releases No releases publ...
Large language models (LLMs) have been recently leveraged as training data generators for various natural language processing (NLP) tasks. While previous research has explored different approaches to training models using generated data, they generally rely on simple class-conditional prompts, which may...
摘要原文 Visual language models (VLMs) rapidly progressed with the recent success of large language models. There have been growing efforts on visual instruction tuning to extend the LLM with visual inputs, but lacks an in-depth study of the visual language pre-training process, where the model...
Extremely large language models like the famousGPT-3 by OpenAIare all the rage. Many of us are now trying to get a sense of scale of the compute that goes into training them. 贼大的语言模型,譬如著名的OpenAI GPT-3现在都很流行。许多人都想知道训练它们大概需要多大计算规模。