Prompt Templates refer to predefined structures or formats that guide the generation of prompts for language models. These templates provide a consistent and standardized way to construct prompts by specifying the desired input and output formats. Prompt templates can include placeholders or variables that...
(30)Let's Verify Step by Step一步步验证(31)Graph of Thoughts: Solving Elaborate Problems with Large Language ModelsGoT,即思维图(32)Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering知识驱动的CoT——KD-CoT(33)Verify-and-Edit: A Knowledge-Enhanced...
第四部分是 LoRA+InstructERC,目标是探索不同基座在InstructERC下的最佳性能表现。 Discriminant Models:我们分别从 Attention,Recurrent,Knowledge,Graph 和 Multimodel中选择表现最优异的模型,可以发现他们的SOTA只集中在某一个数据集,而 InstructERC在三个数据集上均取得了SOTA。 Zero-Shot + InstructERC:从基座的指令...
1.WARM:On the Benefits of Weight Averaged Reward Models 论文地址:https://arxiv.org/abs/2401.12187 在这篇 1 月 22 日的论文《WARM: On the Benefits of Weight Averaged Reward Models》中,研究者提出了一种用于 LLM 奖励模型的权重平均方法。这里的奖励模型是指在用于对齐的 RLHF 中使用的奖励模型。
GQA(Grouped-Query Attention,来自于论文:GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints)在MQA的基础上分成了G个组,组内共享KV。 在Llama2模型中,70B参数为了提升推理性能使用了GQA,其他版本没有使用这项技术。
我这里用megatron举例。megatron框架的模型&优化器存储系数是18，也就是模型参数量*18=显存占用。对于13B...
Deng et al.[4], Figure 1. CC-BY Deng 等人的论文《 DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models (June 2023) 》一文的主要发现是,大语言模型很容易被误导,产生有毒的、存在偏见的输出。 还有其他一些发现包括:
but they're developed and operated by private companies. The source code, training strategies, model weights, and even details like the number of parameters they have are all kept secret. The only ways to access these models are through a chatbot or app built with them, or through an API....
(student.parameters(), lr=0.01, momentum=0.9) # 定义蒸馏的温度和权重 temperature = 2.0 alpha = 0.5 for epoch in range(100): # 进行 100 个训练周期 for i, data in enumerate(trainloader, 0): inputs, labels = data # 计算教师模型的输出 teacher_outputs = teacher(inputs) teacher_probs ...
A large language model utilizes massive datasets, often featuring 100 million or more parameters, in order to solve common language problems. Developed by OpenAI, ChatGPT is one of the most recognizable large language models. Google's BERT, Meta’s Llama 2, and Anthropic's Claude 2 are other...