课程: AutoML: Build Production-Ready Models Quickly!
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Introducing HugginFace AutoTrain - Python教程
课程: AutoML: Build Production-Ready Models Quickly!
Introducing HugginFace AutoTrain
- [Instructor] For this chapter, we will use Hugging Face Auto Train. Like Azure Custom Vision, which we explored in the last chapter. Auto Train offers a no code approach to training, evaluating, and deploying machine learning models. The machine learning models can handle natural language processing tasks, like summarization, translation, and text classification. It can also handle vision tasks like image classification. Auto Train is connected to the Hugging Face hub, which is a platform where machine learning practitioners of all kinds contribute models, data sets, and demos. This makes it easier for us to experiment with open source models that suit our task. We can also take advantage of any of them that meet our objectives. To begin, head over to huggingface.com/autotrain, and sign up for an account, or login to your existing account. Although Auto Train offers a paid plan, a paid pro plan, for this chapter, we are…
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NLP: How do you handle text data?1 分钟 51 秒
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Introducing HugginFace AutoTrain4 分钟 31 秒
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Formatting and uploading your data for your task3 分钟 16 秒
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Training your AutoNLP model and making predictions7 分钟 3 秒
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Challenge: Multi-class text classification1 分钟 5 秒
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Solution: Multi-class text classification4 分钟 45 秒
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