from keras import Sequential
from keras.layers import Flatten,Dense,Dropout
from keras import Inputmodel = Sequential()
model.add(Input(shape=(28,28)))
model.add(Flatten())
model.add(Dense(units=256,kernel_initializer='normal',activation='relu'))
model.add(Dropout(rate=0.1))
model.add(Dense(units=64,kernel_initializer='normal',activation='relu'))
model.add(Dropout(rate=0.1))
model.add(Dense(units=10,kernel_initializer='normal',activation='softmax'))
model.summary()
Ranni: Taming Text-to-Image Diffusion for Accurate Instruction Following
abstract
我们引入了一个语义面板作为解码文本到图像的中间件,支持生成器更好地遵循指令
Related work
最近的工作还通过包含额外的条件(如补全掩码[15,45]、…
CI/CD笔记.Gitlab系列 新用户管理 -
文章信息 -
Author: 李俊才 (jcLee95) Visit me at CSDN: https://jclee95.blog.csdn.netMy WebSite:http://thispage.tech/Email: 291148484163.com. Shenzhen ChinaAddress of this article:https://blog.csdn.net/qq_285502…