Question Answering using Transformers Hugging Face Library || BERT QA Python Demo

Heard of "ChatGPT"?? Perhaps tried it too...

The foundation behind ChatGPT is the transformer architecture. In this video we shall build a question answering model using the transformers library of hugging face

We shall learn to select a pre-trained model depending on our task and build a pipeline to get the desired output

Find the references here:
* Hugging face model hub: https://huggingface.co/models

* Pipeline using hugging face: https://huggingface.co/docs/transform...

* Why transformers are more powerful over other NLP architectures such as RNNs and LSTMs: https://www.linkedin.com/posts/sourav...

If you would like me to prepare a separate video explaining how transformers work and why are they so powerful, comment "interested" below


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Additionally, here are few more useful resources for beginners and curious data enthusiasts

1. kaggle: a platform to learn, practice, compete and win cash prizes [https://www.kaggle.com/]

2. paperswithcode: website presenting the latest in machine learning and data science research and the code implementations [https://paperswithcode.com/]

3. google colab: a platform to run code, build machine learning solutions, explore the capabilities of GPU and TPU without any hassle in setting up the environment: [https://colab.research.google.com/]

Remember, "the greatest investment ever made is investment in self growth and learning"