Are you having a hard time finding a reliable option to Fine-tune Subsidize Text For Free? DocHub is made to make this or any other process built around documents more streamlined. It's easy to explore, use, and make changes to the document whenever you need it. You can access the core features for dealing with document-based tasks, like signing, importing text, etc., even with a free plan. In addition, DocHub integrates with multiple Google Workspace apps as well as services, making document exporting and importing a piece of cake.
DocHub makes it easier to work on documents from wherever you’re. In addition, you no longer need to have to print and scan documents back and forth in order to sign them or send them for signature. All the essential features are at your fingertips! Save time and hassle by completing documents in just a few clicks. Don’t hesitate another minute and give DocHub {a try today!
whats up guys this is Chris mcCormick in this video Im going to be taking us through a tutorial on how to apply Bert to document classification so if youve been following along with my YouTube videos then you know we already kind of covered how to fine tune Bert for sentence classification and so you know arent sentence classification and document classification kind of the same thing yes pretty much the main difference here is that Bert has this limitation around the length of the input text that we feed it so this is gonna be about you know how we address that issue basically and in order to do that were going to need a different data set so for this this notebook were going to be using this data set of Wikipedia comments taken from like the edit pages of Wikipedia they contain personal some of them contain personal attacks from one user to another well talk more about the data set in a bit here but as a as a bonus here at the end of the notebook Im also going to take us thro