last_loss=0forbatch_x,batch_clsindataloader:#图像的像素范围转换到[-1,1],和高斯分布对应batch_x=batch_x.to(DEVICE)*2-1#引导分类IDbatch_cls=batch_cls.to(DEVICE)#为每张图片生成随机t时刻batch_t=torch.randint(0,T,(batch_x.size(0),)).to(DEVICE)#生成t时刻的加噪图片和对应噪音batch_x_t...
CLUEbenchmark/SuperCLUE: SuperCLUE: 中文通用大模型综合性基准 | A Benchmark for Foundation Models in Chinese (github.com)SuperCLUE是一个综合性大模型评测基准,本次评测主要聚焦于大模型的四个能力象限,包括语言理解与生成、专业技能与知识、Agent智能体和安全性,进而细化为12项基础能力。
CLUEbenchmark/SuperCLUE: SuperCLUE: 中文通用大模型综合性基准 | A Benchmark for Foundation Models in Chinese (github.com)SuperCLUE是一个综合性大模型评测基准,本次评测主要聚焦于大模型的四个能力象限,包括语言理解与生成、专业技能与知识、Agent智能体和安全性,进而细化为12项基础能力。 BIG-bench (Beyond ...
模型分析与解释，比如NLP中通过构造特殊生成任务判断模型的fairness以及inductive bias. 又比如直接生成一个...
2 Autoregressive Models) was originally proposed for natural language processing (NLP) task machine translation. Later works show that Transformer-based models can achieve state-of-the-art performances on various tasks, not only in the field of NLP but also in computer vision (CV) [56]. Unlike...
In-context learningis a method of prompt engineering that allows language models to learn tasks ...
you'llgaininsightsintostate-of-the-artmodelsinimagesynthesis,speechenhancement,andnaturallanguagegenerationusingGANs.Inadditiontothis,you'llbeabletoidentifyGANsampleswithTequilaGAN.Bytheendofthisbook,youwillbewell-versedwiththelatestadvancementsintheGANframeworkusingvariousexamplesanddatasets,andyouwillhavetheskills...
而LLM的出现,使得Agents可以通过NLP的方式和外部环境进行交互,而NLP自然语言又是一种极其通用的交互方式,这就大大扩展了Agents的信息感知和交互能力 今天因为有了LLM大模型技术,基于LLM这个“智能大脑”,使得智能代理可以做到很多以前做不到的事情。 LLM给Agents智能体技术带来了两个比较大的改进:...
The proposed approach leverages Large Language Models (LLMs) and traditional machine learning algorithms to handle both structured and unstructured data in each ticket. First, generative models are used to pre-process the ticket data and classify the tickets into different categories. Then, these ...
The emergence of publicly accessible artificial intelligence (AI) large language models such as ChatGPT has given rise to global conversations on the implications of AI capabilities. Emergent research on AI has challenged the assumption that creative pot