# Question Answering no-context **URL:** \ **Category:** Beginners\ **Created:** [April 22, 2024, 5:31pm UTC](https://discuss.huggingface.co/t/question-answering-no-context/83148 "2024-04-22T17:31:34Z")\ **Posts on this page:** 3\ **Page:** 1
**Author:** ![rasdlasdl](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/rasdlasdl/32/26099_2.png) [@rasdlasdl](https://discuss.huggingface.co/u/rasdlasdl)\ **Post date:** [April 22, 2024, 5:31pm UTC](https://discuss.huggingface.co/t/question-answering-no-context/83148/1 "2024-04-22T17:31:34Z")
Hello everyone, I have dataset of medicine questions it looks like [{“question”:question, “answer”:answer}, {“question”:question, “answer”:answer}, …] I neeed to train a model which would give me answer based on my question It should be something like FAQ As input I will provide new question and model should give me one of the answers in dataset I tried to find something similar but only thing I could find was QA with context and Text Classsification Positive or Negative( Any thoughts? Thanks ---
**Author:** ![Namitg02](https://avatars.discourse-cdn.com/v4/letter/n/e8c25b/32.png) [@Namitg02](https://discuss.huggingface.co/u/Namitg02)\ **Post date:** [May 22, 2024, 4:55pm UTC](https://discuss.huggingface.co/t/question-answering-no-context/83148/2 "2024-05-22T16:55:34Z")
Hello, You can probably consider a RAG approach to do this. Thanks ---
**Author:** ![vpkprasanna](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/vpkprasanna/32/26436_2.png) [@vpkprasanna](https://discuss.huggingface.co/u/vpkprasanna)\ **Post date:** [May 22, 2024, 5:09pm UTC](https://discuss.huggingface.co/t/question-answering-no-context/83148/3 "2024-05-22T17:09:08Z")
You can either convert this into csv or a table structure use a [TAPAS](https://huggingface.co/docs/transformers/en/model_doc/tapas) model from google to get the answer or use LLM to get answer using the technique called RAG