Haystack Open-source framework for question answering system Python Google Colab Demo
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- Опубликовано: 10 янв 2025
- In this video I demonstrate how Haystack can be used to build search systems. I use Haystack on MIMIC clinical data to build a simple search and question answering engine
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Hi Rithesh,
Thanks. Nice video and a good overview of concepts. Recently I am also exploring Haystack use cases.
Thank You Pradip!
great teacher, thank you brother
Thank You
Hi Rithesh, Thanks for the video.
Thank You
How we can implement the google collab code of QnA model in a web application?
You need to create and expose a REST api. There are different ways of doing it
what about my document i want i asked question from my document ,,,model is able to genearte long answers
Have a look at haystack documentation to see if there is a parameter that can be modified for long answers
Hi Rithesh,
How to fine tune and deploy this model on aws or on any cloud service?
Please read haystack documentation
Can I know how we can collect the datasets for the nlp on a specific topic?? I am exploring haystack for nlp now. Pls do help
There is a website index.quantumstat.com/
Where can I get this dataset?
Have a look at this video:ruclips.net/video/uYj-uP6CQnA/видео.html
Very nice thank you
Thank You!
very helpful, concept clearing video for me. thanks for it. but i want to know two things here plz help me in it. actually i am facing error in unzipping the file , i tried it many times. and i also want to know how can i do the same process in pdf file actually i need to insert the pdf file instead of document file , i am following the same process that you explained but getting error. please tell me .
I am not sure of pdf support in haystack. Check the documentation . Otherwise you need to use python libraries to parse pdf into text
@@RitheshSreenivasan thanks ritesh. please tell me the unzipping also i got error.
Hi Rithesh,
You videos are very informative,
I am currently working in this domain but we have prefer not to use full managed systems like haystack.
The question that I want to ask you is that, When choosing the deep learning model for the embedding what do you consider apart from the available benchmark.
I our use case we have choose mpnet v2
It will be much helpful if you can share your thoughts :)
Much love,
Rajdeep
I have generally used BERT based embeddings
@@RitheshSreenivasan but Does BERT able to handle huge request
The reason we choose mpnet v2 is because of the performance by trading the speed(QPS).
Use whatever works for you. If the text is related to the domain on which the embeddings were trained then you might get fewer out of vocabulary words
is this free? can i run this in my local and create Q and A?
Yes it is open source. Check system requirements in their GitHub page
Thanks
Thank You