Build your own language models for intelligent enterprise generative AI applications. Content Generation Marketing content Product description generation Summarization Legal paraphrasing Meeting notes summarization Chatbot Question and answering Customer service agent Information Retrieval Passage retrieval and...
OpenAI releasedGPT-3, a 175 billion-parameter model that generated text and code with short written prompts.In 2021, NVIDIA and Microsoft developed Megatron-Turing Natural Language Generation 530B, one of the world’s largest models for reading comprehension and natural language inference, with 530...
Experimental results on three real datasets for summarization show that our model is highly competitive and has a very high consistency with human annotators.doi:10.1007/978-3-031-44693-1_54Wu, NingGong, MingShou, LinjunLiang, ShiningJiang, Daxin...
Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature. This study delves into the potential of large language models (LLMs) for binary code comprehension. To this end, ...
Artificial intelligence (AI) has significantly impacted various fields. Large language models (LLMs) like GPT-4, BARD, PaLM, Megatron-Turing NLG, Jurassic-
How Large Language Models Are Trained Training LLMs requires sizable volumes of data and considerable computing horsepower, especially for models that use many parameters. Depending on the intended use case for the LLM, it could be trained on a general-purpose dataset that includes a wide range ...
Large language models (LLMs) are deep learning algorithms that are trained on Internet-scale datasets with hundreds of billions of parameters. LLMs can read…
It also creates codes and natural language about code from prompts. LlaMA best features Perform NLP tasks such as text generation, comprehension, summarization, and translation Built as an open-source large language model (LLM) designed for developers, researchers, and businesses to build, experiment...
LLMs have set new benchmarks in various NLP tasks, including sentiment analysis, question-answering, machine translation, text summarization, and more. Their ability to leverage massive amounts of training data and learn intricate language patterns empowers them to outperform traditio...
论文分享:Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approach 强化学习实验室 官网:http://rl.beiyang.ren 16 人赞同了该文章 文中希望借助LLM来解决星际的复杂任务,实现长期的任务规划和策略可解释性。因此,文中实现了TextStarCraft II,为星际实现了文本转换的接口...