PyTorch vs TensorFlow in 2022

Data Science And Machine Learning Machine Learning Data Science

PyTorch Landing Page
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PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
Pricing:
- Open Source
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of the water. Almost 85% of models are PyTorch exclusive, and even those that are not exclusive have about a 50% chance of being available in PyTorch as well. In contrast, only about 16% of all models are available for TensorFlow, with only about 8% being TensorFlow-exclusive.

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TensorFlow Landing Page
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TensorFlow

TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Pricing:
- Open Source
There are a couple of notable exceptions to this rule, the most notable being that those in Reinforcement Learning should consider using TensorFlow. TensorFlow has a native Agents library for Reinforcement Learning, and Deepmind’s Acme framework is implemented in TensorFlow. OpenAI’s Baselines model repository is also implemented in TensorFlow, although OpenAI’s Gym can be used with either TensorFlow or PyTorch. If you plan to use TensorFlow for your research, you should also check out Deepmind’s Sonnet for higher-level abstractions.

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