There’s sooo much content to take in these days.
Blog posts coming out left, right and centre.
KZitem videos to watch
Podcasts to listen to.
Don’t you sometimes wish you could just get a summary of them all?
Well, you can!
Using Hugging Face Transformers you can leverage a pre-trained summarisation pipeline to start summarising content. In fact in just 4 lines of Python code you can begin to summarise blog posts. It’s ridiculously easy to get started with and the fun just begins there, there’s so much more stuff you can do with the Hugging Face Transformers library!
In this video you'll go through:
1. Installing Hugging Face Transformers
2. Building a summarization pipeline
3. Running an encoding decoding model for summarization
Get the CODE: github.com/nicknochnack/Huggi...
Chapters
0:00 - Start
1:09 - Installing Hugging Face Transformers
3:12 - Loading the Summarization Pipeline
4:20 - Generating a Summary
Oh, and don't forget to connect with me!
LinkedIn: / nicholasrenotte
Facebook: / nickrenotte
GitHub: github.com/nicknochnack
Happy coding!
Nick
P.s. Let me know how you go and drop a comment if you need a hand!
Негізгі бет Ғылым және технология AI Text Summarization with Hugging Face Transformers in 4 Lines of Python
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