Parameter | Value |
---|---|
OS | Ubuntu 20.04.5 |
Python | 3.8.10 |
CUDA | 11.8 |
TensorFlow | 2.10.1 |
TensorRT | 8.5.1 |
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import tensorflow as tf | |
from tensorflow.keras import layers | |
model = tf.keras.Sequential([ | |
layers.Conv2D(32, kernel_size=(3, 3),activation='relu', | |
layers.MaxPool2D((2, 2)), | |
layers.Conv2D(64,kernel_size=(3, 3), activation='relu'), | |
layers.MaxPool2D((2, 2)), | |
layers.Dropout(0.2), | |
layers.GlobalAveragePooling2D(), |
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Work | Details |
---|---|
Augmenting convnets with aggregated attention | Tutorial by Aritra |
Train a Vision Transformer on small datasets | Tutorial by Aritra |
MobileViT | Tutorial by Sayak |
Compact Convolutional Transformers | Tutorial by Sayak |
Data efficient image transformers | TF implementation, TF pre-trained models, tutorial by Sayak |
Class attention image transformers | TF implementation, TF pre-trained models by Sayak |
Masked Autoencoders | TF implementation, tutorial by Aritra and Sayak, Contribution to Hugging Face Transformers by Aritra and Sayak |
Probing the representation of ViTs |