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runtime
A performant and modular runtime for TensorFlow
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cleverhans
An adversarial example library for constructing attacks, building defenses, and benchmarking both
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tfjs-examples
Examples built with TensorFlow.js
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datasets
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
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tensorflow
An Open Source Machine Learning Framework for Everyone
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io
Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO
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serving
A flexible, high-performance serving system for machine learning models
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probability
Probabilistic reasoning and statistical analysis in TensorFlow
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docs-l10n
Translations of TensorFlow documentation
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tfx
TFX is an end-to-end platform for deploying production ML pipelines
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addons
Useful extra functionality for TensorFlow 2.x maintained by SIG-addons
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agents
TF-Agents is a library for Reinforcement Learning in TensorFlow
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tfjs
A WebGL accelerated JavaScript library for training and deploying ML models.
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models
Models and examples built with TensorFlow
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ngraph-bridge
TensorFlow-nGraph bridge
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mesh
Mesh TensorFlow: Model Parallelism Made Easier
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tensorboard
TensorFlow's Visualization Toolkit
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model-card-toolkit
a tool that leverages rich metadata and lineage information in MLMD to build a model card
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text
Making text a first-class citizen in TensorFlow.
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tensorrt
TensorFlow/TensorRT integration
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cloud
The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud.
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federated
A framework for implementing federated learning
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swift-models
Models and examples built with Swift for TensorFlow
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hub
A library for transfer learning by reusing parts of TensorFlow models.
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model-optimization
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
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model-remediation
Model Remediation is a library that provides solutions for machine learning practitioners working to create and train models in a way that reduces or eliminates user harm resulting from underlying performance biases.