Model training Archives | Tecton

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Training Large-Scale Recommendation Models with TPUs

At Snap, we train a large number of deep learning models every day to continuously improve the ad recommendation quality to Snapchatters and provide more value to the advertisers. These ad ranking models have hundreds of millions of parameters and are trained on billions of examples. Training an ad ranking model is a computation-intensive and memory-lookup-heavy task. It requires a state-of-the-art distributed system and performant hardware to complete the training reliably and in a timely manner. This session will describe how we leveraged Google’s Tensor Processing Units (TPU) for fast and efficient training. … Read More

Are Transformers Becoming the Most Impactful Technology of the Decade?

In this presentation, Clément will provide insights into the revolution taking place in the open-source community with machine learning. From the CEO who is on a mission to create the “Github of Machine Learning,” learn how the best-in-class companies and talent are using Hugging Face’s tools, and why the open source approach is particularly powerful in doing so. … Read More

Streamlining NLP Model Creation and Inference

At Primer we deliver applications with cutting-edge NLP models to surface actionable information from vast stores of unstructured text. The size of these models and our applications’ latency requirements create an operational challenge of deploying a model as a service. Furthermore, creation/customization of these models for our customers is difficult as model training requires the procurement, setup, and use of specialized hardware and software. Primer’s ML Platform team solved both of these problems, model training and serving, by creating Kubernetes operators. In this talk we will discuss why we chose the Kubernetes operator pattern to solve these problems and how the operators are designed. … Read More

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