Models

On the Opportunities and Risks of Foundation Models

引用链接:https://zhuanlan.zhihu.com/p/401157815 论文链接:https://arxiv.org/pdf/2108.07258.pdf 正文分四部分,阐述内容如下: 能力:模型的能力,模型可以做到的事 语言、视觉、机器人学、推理、交互、理解等; 应用:可应用领域 ......
Opportunities Foundation Models Risks the

Conditional Probability Models for Deep Image Compression

\(\quad\)在自编码器中使用深度网络已成为有前途的研究方向,这种学习网络有两个挑战: 处理量化与控制reconstruction error (distortion) entropy (rate) of the latent image representation之间的权衡(rate都用熵表 ......

Django——models中配置级联更新级联删除

代码如下: models.ForeignKey(to='Publish') models.ForeignKey(on_delete=models.CASCADE, on_update=models.CASCADE) ......
Django models

An invitation to 3-d vision: from images to geometric models英文pdf下载

Ma Y, Soatto S, Košecká J, et al. An invitation to 3-d vision: from images to geometric models[M]. New York: springer, 2004. https://www.eecis.udel.ed ......
invitation geometric images models vision

[论文阅读] Latent Consistency Models@ Synthesizing High-Resolution Images with Few-Step Inference

1. Pre title: Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference accepted: arXiv 2023 (ICLR 2024 Submission) paper ......

Adding Conditional Control to Text-to-Image Diffusion Models

https://mp.weixin.qq.com/s/iL6YitT7EGP6DnrBehb9MQ 1.Adding Conditional Control to Text-to-Image Diffusion Models 论文地址:https://arxiv.org/pdf/2302.05543 ......

【论文阅读笔记】【OCR-文本识别】 Scene Text Recognition with Permuted Autoregressive Sequence Models

PARSeq ECCV 2022 读论文思考的问题 论文试图解决什么问题? 一些文本识别模型会对 semantic 信息建模,从而辅助某些困难情况下的文本识别 传统的 auto-regressive 方式限制了语义信息的传输方向;双向的 auto-regressive 聚合增加了不必要的计算量和复杂 ......

langchain中的chat models介绍和使用

简介 之前我们介绍了LLM模式,这种模式是就是文本输入,然后文本输出。 chat models是基于LLM模式的更加高级的模式。他的输入和输出是格式化的chat messages。 一起来看看如何在langchain中使用caht models吧。 chat models的使用 首先langchai ......
langchain models chat

Transformer-based Encoder-Decoder Models

整理原链接内容方便阅读 https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/Encoder_Decoder_Model.ipynb title: "Transformer-based Enco ......

执行这个这个命令sh download_depth_models.sh【记录】

要下载上述模型,自己的电脑执行不了sh命令。 网上先下载git这个软件。 sh.exe用这个软件来运行 cd到 download_depth_models.sh这个文件所在的路径 再sh download_depth_models.sh执行这个命令! 方法二: 直接用记事本打开这个文件downloa ......

Conditional Probability Models for Deep Image Compression

深度神经网络被训练来作为图像压缩的自动编码器是一个前沿方向,面临的挑战有两方面——量化(quantization)和权衡reconstruction error (distortion) and entropy (rate),这篇文章关注后者。 主要思想是使用上下文模型直接对潜在表示的熵建模;3D- ......

Conditional Probability Models for Deep Image Compression

深度神经网络被训练来作为图像压缩的自动编码器是一个前沿方向,面临的挑战有两方面——量化(quantization)和权衡reconstruction error (distortion) and entropy (rate),这篇文章关注后者。 主要思想是使用上下文模型直接对潜在表示的熵建模;3D- ......

Internet-augmented language models through few-shot prompting for open-domain question answering阅读笔记

Internet-augmented language models through few-shot prompting for open-domain question answering 其实我没怎么正经读过论文,尤其是带实验的,我目前认真读过的(大部头)也就是一些LLM的综述。记录这个文档主 ......

Running Large Language Models locally – Your own ChatGPT-like AI in C#

For the past few months, a lot of news in tech as well as mainstream media has been around ChatGPT, an Artificial Intelligence (AI) product by the fol ......

IDM:Implicit Diffusion Models for Continuous Super-Resolution超分辨率

摘要 当今超分辨领域的模型普遍存在过度平滑(难以保持放大后图像的锐利和纹理,导致高频信息丢失和视觉上变得平滑)和伪影(生成的高分辨率图像中可能出现的不希望出现的失真或瑕疵,包括模糊、马赛克效应或者不自然纹理等)的现象,作者据此提出了IDM模型,IDM模型是在一个统一的端到端框架中集成了隐式神经表示和 ......

ModuleNotFoundError: No module named 'models'

首先看看是不是用户自己的包,如果不是再安装网上的包。 ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 45 42 import keras_metrics as km 43 from keras.model ......
ModuleNotFoundError module models named 39

论文阅读(二)—— Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators

![image](https://img2023.cnblogs.com/blog/3279428/202310/3279428-20231009200651960-1205649789.png) ![image](https://img2023.cnblogs.com/blog/3279428/2... ......

论文阅读(一)——Adding Conditional Control to Text-to-Image Diffusion Models

![image](https://img2023.cnblogs.com/blog/3279428/202310/3279428-20231009200344161-887129974.png) ![image](https://img2023.cnblogs.com/blog/3279428/20... ......

Black-Box Attack-Based Security Evaluation Framework forCredit Card Fraud Detection Models

Black-Box Attack-Based Security Evaluation Framework forCredit Card Fraud Detection Models 动机 AI模型容易受到对抗性攻击(对样本添加精心设计的扰动生成对抗性示例) 现有的对抗性攻击可以分为白盒攻击和黑盒攻击 ......

Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System

目录概符号说明Ranking Distillation代码 Tang J. and Wang K. Ranking Distillation: Learning compact ranking models with high performance for recommender system. ......

GPT之路(八) LangChain - Models入门

环境:Python 3.11.4, LangChain 0.0.270, Jupyter Models模型简介 官方地址:LangChian - Models Langchain所封装的模型分为两类: 大语言模型 (LLM) 聊天模型 (Chat Models) Langchain的支持众多模型供应 ......
LangChain Models GPT

[论文速览] SDXL@ Improving Latent Diffusion Models for High-Resolution Image Synthesis

Pre title: SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis accepted: arXiv 2023 paper: https://arxiv.org/abs/2307.01952 co ......

Training language models to follow instructions with human feedback

郑重声明:原文参见标题,如有侵权,请联系作者,将会撤销发布! NeurIPS 2022 ......

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models 阅读笔记(11.2) 摘要:优化MSE指标通常会导致模糊,特别是在高方差(详细)区域。我们提出了一种基于创建正确降尺度的 ......

Models List of Traffic Forecasting

模型列表 基线模型 对于时间序列预测任务:(模型在test/目录下) HA: 历史平均值,将历史流量建模为季节性过程,然后使用前几个季节的加权平均值作为预测值。 VAR: 向量自回归,这是一种常用的时间序列预测模型,用于捕捉多个变量随时间的关系。 SVR: 支持向量回归,它使用线性支持向量机进行回归 ......
Forecasting Traffic Models List of

Typical Models of RNN and TFF

RNN LSTM(2014) Recurrent Neural Networks Hidden State: \(h\) \(h_t = tanh(U h_{t-1} + W x_t + b)\) \(y_t = Vh_t\) h: history state tanh : active funct ......
Typical Models RNN TFF and

django之models

#字段选项 null 如果是 True, Django 将在数据库中存储空值为 NULL。默认为 False。 blank 如果是 True ,该字段允许为空。默认为 False 。 choices from django.db import models class Student(models. ......
django models

《PROMPT2MODEL: Generating Deployable Models from Natural Language Instructions》论文学习

一、Introduction 传统上,从零开始构建一个自然语言处理(NLP)模型是一项重大任务。一个寻求解决新问题的NLP从业者需要定义他们的任务范围,找到或创建目标任务领域的行为数据,选择合适的模型架构,训练模型,通过评估评估其性能,然后将其部署到实际应用中。 Prompt2Model is a ......

Proj CDeepFuzz Paper Reading: PELICAN: Exploiting Backdoors of Naturally Trained Deep Learning Models In Binary Code Analysis

## Abstract 背景: 1. 本文研究的不是被恶意植入的后门,而是products of defects in training 2. 攻击模式: injecting some small fixed input pattern(backdoor) to induce misclassifi ......

通过提示大语言模型进行个性化推荐LLM-Rec: Personalized Recommendation via Prompting Large Language Models

论文原文地址:https://arxiv.org/abs/2307.15780 本文提出了一种提示LLM并使用其生成的内容增强推荐系统的输入的方法,提高了个性化推荐的效果。 ## LLM-Rec Prompting ![](https://img2023.cnblogs.com/blog/17994 ......