This repository contains machine learning models implemented in TensorFlow. The models are maintained by their respective authors. To propose a model for inclusion, please submit a pull request.

Alex Alemi e46ec60235 Update inception_resnet_v2.py 9 rokov pred
.github dc7791d01c Create ISSUE_TEMPLATE.md (#124) 9 rokov pred
autoencoder a472ac9525 merged changes from #25 10 rokov pred
compression 199db00e33 Merge pull request #510 from nickj-google/master 9 rokov pred
differential_privacy a374c26e6a Fix the BUILD file 9 rokov pred
im2txt 0cba7a4b5d Remove comment that TensorFlow must be built from source. 9 rokov pred
inception bf51d43420 fix module object has no attribute NodeDef for tensorflow 0.11 (#572) 9 rokov pred
lm_1b fdc4ce37a4 Fix README 9 rokov pred
namignizer 76f567df5f add the namignizer model (#147) 9 rokov pred
neural_gpu a803bf4171 Add to neural_gpu documentation. 9 rokov pred
resnet d93ffd0b69 Allow softplacement for ResNet 9 rokov pred
slim e46ec60235 Update inception_resnet_v2.py 9 rokov pred
street f42469ef90 Updated download instructions to match reality 9 rokov pred
swivel f3144eb061 Add sys.stdout.flush() 9 rokov pred
syntaxnet 5eff490de4 Fix POS tagging score of Ling et al.(2005) 9 rokov pred
textsum 5e875226bc Explicitly set state_is_tuple=False. 9 rokov pred
transformer d816971032 Use tf.softmax_cross_entropy_with_logits to calculate loss (#181) 9 rokov pred
video_prediction d67ea24901 video prediction model code 9 rokov pred
.gitignore 3e6caf5ff0 Add a .gitignore file. (#164) 9 rokov pred
.gitmodules 32ab5a58dd Adding SyntaxNet to tensorflow/models (#63) 9 rokov pred
AUTHORS 41c52d60fe Spatial Transformer model 10 rokov pred
CONTRIBUTING.md d84df16bc3 fixed contribution guidelines 10 rokov pred
LICENSE 7c41e653dc Update LICENSE 10 rokov pred
README.md 4f9d102483 Open source the image-to-text model based on the "Show and Tell" paper. 9 rokov pred
WORKSPACE ac0829fa2b Consolidate privacy/ and differential_privacy/. 9 rokov pred

README.md

TensorFlow Models

This repository contains machine learning models implemented in TensorFlow. The models are maintained by their respective authors.

To propose a model for inclusion please submit a pull request.

Models

  • autoencoder -- various autoencoders
  • inception -- deep convolutional networks for computer vision
  • namignizer -- recognize and generate names
  • neural_gpu -- highly parallel neural computer
  • privacy -- privacy-preserving student models from multiple teachers
  • resnet -- deep and wide residual networks
  • slim -- image classification models in TF-Slim
  • swivel -- the Swivel algorithm for generating word embeddings
  • syntaxnet -- neural models of natural language syntax
  • textsum -- sequence-to-sequence with attention model for text summarization.
  • transformer -- spatial transformer network, which allows the spatial manipulation of data within the network
  • im2txt -- image-to-text neural network for image captioning.