Tour of Upcoming Features on the Hugging Face Model Hub // Julien Chaumond // MLOps Coffee Sessions #48 from Agentic Conversations (formally mlops.community)

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Tour of Upcoming Features on the Hugging Face Model Hub // Julien Chaumond // MLOps Coffee Sessions #48

52 minutes Posted Jul 27, 2021 at 10:09 am.

] Introduction to Julien Chaumond

] Julien's background in tech

] "I have this vision of building a community where the greatest people in AI can come together and basically invent the future of Machine Learning together."

] What is Hugging Face?

] "We have the goal of bridging the gap between research and production on actual production use cases."

] Start of open-source in Hugging Face

] Chatbox experiment (reference resolution system) linking pronouns to the subjects of sentences

] From a project to a company

] "The goal was to explore in the beginning."

] Importance of platform

] "Transfer learning is an efficient way of Machine Learning. Providing your platform  around change that people want to start from pre-trained model and fine-tune them into the specific use case is something that can be big so we built some stuff to help people do that."

] Narrowing down the scope of service to provide

] "We have some vision of what we want to build but a lot of it is the small incremental improvements that we bring to the platform. I think it's the natural way of building stuff nowadays because Machine Learning is moving so fast."

] Model Hubs

] "We're guaranteeing that we don't build anything that introduces any lagging to Hugging Face because we're using Github. You'll have that peace of mind."

] Storing model artifacts

] AWS cache - stored to an edge location all around the globe

] Inference widgets powering

] "For each model on the model hub we try to ensure that we have the metadata about the model to be able to actually run it."

] Deploying infra function

] "Depending on the model and library, we optimize the custom containers to make sure that they run as fast as possible on the target hardware that we have."   

] "Machine Learning is still pretty much hardware dependent."

] Hardware usage

] "CPU is super cheap. If you are able to run Berks served with a 1-millisecond on CPU because you have powerful optimizations, you don't really need GPUs anymore. It's cost-efficient and energy-efficient."  

] Challenges of Hugging Face and what you learned

] "It may sound like a super cliche but the team that you assembled is everything."

] War stories in Hugging Face

] "Our goal is more forward-looking to be helpful as much as we can to the community."

] Hugging Face accessibility

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Coffee Sessions #48 with Julien Chaumond, Tour of Upcoming Features on the Hugging Face Model Hub.

//Abstract

Julien Chaumond’s Tour of Upcoming Features on the Hugging Face Model Hub. Our MLOps community guest in this episode is Julien Chaumond the CTO of Hugging Face - every data scientist’s favorite NLP Swiss army knife.

Julien, David, and Demetrios spoke about many topics including:

Infra for hosting models/model hubs

Inference widgets for companies with CPUs & GPUs (for companies)

Auto NLP which trains models

“Infrastructure as a service”

// Bio

Julien Chaumond is Chief Technical Officer at Hugging Face, a Brooklyn and Paris-based startup working on Machine learning and Natural Language Processing, and is passionate about democratizing state-of-the-art AI/ML for everyone.

--------------- ✌️Connect With Us ✌️ -------------

Join our slack community: https://go.mlops.community/slack

Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/

Connect with David on LinkedIn: https://www.linkedin.com/in/aponteanalytics/

Connect with Julien on LinkedIn: https://www.linkedin.com/in/julienchaumond/

Timestamps:

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