Hugging Face's TensorFlow Philosophy

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Hugging Face outlines its TensorFlow philosophy, emphasizing Keras models, flexible loss functions, and pre-built data pipelines

intermediate Published 12 Aug 2022
Action Steps
  1. Use Keras Model objects for all TensorFlow models
  2. Use Keras Layer objects for all TensorFlow layers
  3. Utilize pre-built loss functions and modify them as needed
  4. Leverage pre-built data pipelines for common tasks
  5. Explore XLA for optimized model performance
Who Needs to Know This

This philosophy benefits machine learning engineers and data scientists on a team by providing a standardized approach to building and deploying TensorFlow models, making it easier to collaborate and integrate models into larger projects

Key Insight

💡 Standardizing on Keras models and pre-built components can streamline TensorFlow development and improve collaboration

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🤖 Hugging Face's TensorFlow philosophy: Keras models, flexible loss functions, and pre-built data pipelines for efficient ML development

Key Takeaways

Hugging Face outlines its TensorFlow philosophy, emphasizing Keras models, flexible loss functions, and pre-built data pipelines

Full Article

Published Time: 2022-08-12T00:00:00.115Z

# Hugging Face's TensorFlow Philosophy

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# [](https://huggingface.co/blog/tensorflow-philosophy#hugging-faces-tensorflow-philosophy) Hugging Face's TensorFlow Philosophy

Published August 12, 2022

[Update on GitHub](https://github.com/huggingface/blog/blob/main/tensorflow-philosophy.md)

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### [](https://huggingface.co/blog/tensorflow-philosophy#introduction) Introduction

* [Introduction](https://huggingface.co/blog/tensorflow-philosophy#introduction "Introduction")

* [Interlude: 30 Seconds to 🤗](https://huggingface.co/blog/tensorflow-philosophy#interlude-30-seconds-to-%F0%9F%A4%97 "Interlude: 30 Seconds to 🤗")
* [Philosophy #1: All TensorFlow models should be Keras Model objects, and all TensorFlow layers should be Keras Layer objects.](https://huggingface.co/blog/tensorflow-philosophy#philosophy-1-all-tensorflow-models-should-be-keras-model-objects-and-all-tensorflow-layers-should-be-keras-layer-objects "Philosophy #1: All TensorFlow models should be Keras Model objects, and all TensorFlow layers should be Keras Layer objects.")

* [Philosophy #2: Loss functions are provided by default, but can be easily changed.](https://huggingface.co/blog/tensorflow-philosophy#philosophy-2-loss-functions-are-provided-by-default-but-can-be-easily-changed "Philosophy #2: Loss functions are provided by default, but can be easily changed.")

* [~~Philosophy~~ Implementation Detail #3: Labels are flexible](https://huggingface.co/blog/tensorflow-philosophy#philosophy-implementation-detail-3-labels-are-flexible "Philosophy Implementation Detail #3: Labels are flexible")

* [Philosophy #4: You shouldn’t have to write your own data pipeline, especially for common tasks](https://huggingface.co/blog/tensorflow-philosophy#philosophy-4-you-shouldnt-have-to-write-your-own-data-pipeline-especially-for-common-tasks "Philosophy #4: You shouldn’t have to write your own data pipeline, especially for common tasks")

* [Philosophy #5: XLA is great!](https://huggingface.co/blog/tensorflow-philosophy#philosophy-5-xla-is-great "Philosophy #5: XLA is great!")

* [Philo
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