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How Open Source Transformers Are Accelerating AI - CitC Episode 261

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Content provided by Intel Corporation. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Intel Corporation or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Jeff Boudier from Hugging Face joins host Jake Smith to talk about the company’s open source machine learning transformers (also known as “pytorch-pretrained-bert”) library. Jeff talks about how transformers have accelerated the proliferation of natural language process (NLP) models and their future use in objection detection and other machine learning tasks. He goes into detail about Optimum—an open source library to train and run models on specific hardware, like Intel Xeon CPUs, and the benefits of the Intel Neural Compressor, which is designed to help deploy low-precision inference solutions. Jeff also announces Hugging Face’s new Infinity solution that integrates the inference pipeline to achieve results in milliseconds wherever Docker containers can be deployed. For more information, visit: https://hf.co/ Follow Jake on Twitter at: https://twitter.com/jakesmithintel
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296 episodes

Artwork
iconShare
 
Manage episode 306329631 series 1180916
Content provided by Intel Corporation. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Intel Corporation or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Jeff Boudier from Hugging Face joins host Jake Smith to talk about the company’s open source machine learning transformers (also known as “pytorch-pretrained-bert”) library. Jeff talks about how transformers have accelerated the proliferation of natural language process (NLP) models and their future use in objection detection and other machine learning tasks. He goes into detail about Optimum—an open source library to train and run models on specific hardware, like Intel Xeon CPUs, and the benefits of the Intel Neural Compressor, which is designed to help deploy low-precision inference solutions. Jeff also announces Hugging Face’s new Infinity solution that integrates the inference pipeline to achieve results in milliseconds wherever Docker containers can be deployed. For more information, visit: https://hf.co/ Follow Jake on Twitter at: https://twitter.com/jakesmithintel
  continue reading

296 episodes

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