Datasets:
jamescalam
/
youtube-transcriptions

Dataset card Data Studio Files
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How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t512.0
And then we'll fill this out afterwards.
512
516.72
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t513.52
And then we'll fill this out afterwards.
513.52
524.24
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t520.72
Of course, we do actually need to include the path.
520.72
526.72
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t525.84
So let's take this.
525.84
537.92
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t526.72
And now we can see what's inside here.
526.72
549.44
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t544.24
Maybe we can load just a few rather than all of them.
544.24
554.96
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t549.44
Or we can investigate it like this.
549.44
562.72
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t556.6400000000001
Okay, so we have the version and data, which we can actually see over here.
556.64
564.24
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t563.2800000000001
Version and data.
563.28
566.24
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t564.24
So we want to access the data.
564.24
571.28
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t566.24
And within data, we have a list of all these different items, which is what I was trying
566.24
571.92
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t571.2800000000001
to do before.
571.28
581.28
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t571.92
So we go into data and just take a few of those.
571.92
585.92
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t582.4799999999999
Okay, and then we get our different sections.
582.48
591.68
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t586.64
First one, let's just take zero, which is Beyonce.
586.64
594.16
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t593.04
And then we have all of these.
593.04
600.4
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t595.1999999999999
So we're going to want to loop through each one of these because we have
595.2
606.8
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t600.4
this one, the next, and we're going to keep needing to just run through all of these.
600.4
611.6
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t608.8
So let's do that.
608.8
618.56
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t612.4
We want to do for group in squad dict.
612.4
622.64
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t618.56
And remember, we need to include the data here.
618.56
628.4
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t624.8
Let's just see how, say group title.
624.8
632
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t628.4
So group title, so we can see a few of those.
628.4
635.36
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t632.8
Okay, we're going to go through each one of those.
632.8
642.16
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t637.12
So the second part of that are these paragraphs.
637.12
646.96
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t642.9599999999999
And within the paragraphs, we have each one of our questions.
642.96
658.56
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t646.96
So let's first go with paragraphs and we'll do a chop in here.
646.96
663.6
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t662.5600000000001
Sorry, it's a list.
662.56
664.08
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t663.6
There we go.
663.6
671.76
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t666.72
And the first thing we need to extract is the easiest one, which is our context.
666.72
677.12
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t671.76
However, that is also within a list.
671.76
680.72
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t677.12
So now if we access the context, we get this.
677.12
689.36
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t682.0
So we're essentially going to need to jump through or loop through each one of these here.
682
694
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t690.16
Now we're going to access the paragraphs and loop through each one of those.
690.16
696.96
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t694.0
And then here, we're going to access the context.
694
701.76
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t696.96
So let's write that.
696.96
705.28
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t701.76
So we already have one group here.
701.76
706.72
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t705.2800000000001
So let's just stick with that.
705.28
714.96
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t708.5600000000001
And we're going to run through the passage in the paragraphs.
708.56
720.72
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t715.76
So already here, we're going through the for loop on this index.
715.76
723.68
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t720.72
And now we're going to go through the for loop.
720.72
728.56
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t723.68
And now we're going to go through a loop on this index.
723.68
737.84
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t735.1999999999999
Let's keep that.
735.2
746.48
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t739.12
So that means that we will be able to print the passage context.
739.12
749.68
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t749.04
And there we go.
749.04
751.68
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t750.24
So here we have all of our context.
750.24
755.76
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t751.68
So that's one of our three items that we need to extract.
751.68
757.76
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t756.9599999999999
Okay, so that's great.
756.96
759.68
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t757.76
Let's put that all together.
757.76
764
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t760.4799999999999
So we're going to take this, put it here.
760.48
768.64
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t765.3599999999999
And then we have our context.
765.36
774
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t773.12
Okay, that's great.
773.12
778.88
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t774.8
But obviously for each context, we have a few different questions and answers.
774.8
782
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t778.88
So we need to get those as well.
778.88
786.08
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t782.0
Now, that requires us to go through another for loop.
782
788.08
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t786.08
So let's go this passage.
786.08
795.76
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t788.72
We need to go into the QAS key and loop through this list of question and answers.
788.72
802.08
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t797.84
So we have this, and then we have our list.
797.84
811.2
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t802.08
So another layer in our for loop will be for question answer in passage QAS.
802.08
816.64
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t813.9200000000001
And then let's take a look at what we have there.
813.92
817.84
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t817.2800000000001
Okay, great.
817.28
823.12
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t817.84
So we have plausible answers, question and answers.
817.84
828.96
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t824.08
So what we want in here is the question and answers.
824.08
831.28
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t828.96
So question is our first one.
828.96
834.64
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t834.1600000000001
Perfect.
834.16
836.8
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t834.64
So we have the questions now.
834.64
857.2
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t854.08
And then after we have extracted the question,
854.08
859.12
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t857.2
we can move on to our answers.
857.2
863.68
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t860.0
As we see here, the answers comes as another list.
860
868.08
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t864.24
Now each one of these lists all just have one actual answer in there,
864.24
870
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t869.0400000000001
which is completely fine.
869.04
872
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t870.0
So we can access that in two ways.
870
878.4
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t872.0
We can either loop through or we can access the zero value of that array.
872
881.12
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t879.44
Either way, it doesn't matter.
879.44
884.88
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t883.12
So all we need to do here
883.12
894.48
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t884.88
is loop through those answers or if we want just go with QA answers 0.
884.88
902.56
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t899.28
So in most cases, this should be completely fine.
899.28
910.32
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t904.8
As we can see here, most of these question and then they have the answers dictionary.
904.8
915.2
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t910.32
The question and then they have the answers dictionary, which is fine.
910.32
920.64
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t917.0400000000001
However, some of these are slightly different.
917.04
925.84
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t923.2800000000001
So if we scroll right down to the end here,
923.28
932.64
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t928.88
see, okay, we have this which is talking about physics.
928.88
936.64
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t932.64
And then rather than having our answers array, we have these plausible answers,
932.64
940.64
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t938.16
which is obviously slightly different.
938.16
944.16
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t941.68
And this is the case for a couple of those.
941.68
948.96
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t945.4399999999999
So from what I've seen to state, it's like the best way to deal with this
945.44
952.64
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t949.84
is simply to have a check.
949.84
956.72
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t952.64
If there is a plausible answers key within the dictionary,
952.64
959.68
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t957.4399999999999
we will include that as a check.
957.44
963.36
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t959.68
Within the dictionary, we will include that as the answer
959.68
965.92
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t963.3599999999999
rather than the actual answers dictionary.
963.36
978.32
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t967.1999999999999
So to do that, all we need to do is check if QA keys contains plausible answers.
967.2
979.44
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t978.3199999999999
If it does, we use that.
978.32
991.04
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t979.44
Otherwise, we use answers.
979.44
991.36
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t991.0400000000001
Okay.
991.04
999.28
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t998.4000000000001
Then we use this one.
998.4
1,002.08
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t1001.44
Otherwise,
1,001.44
1,009.2
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t1002.08
we will use answers.
1,002.08
1,016.24
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t1011.9200000000001
So let's just add all of that into our for loop here.
1,011.92
1,022.4
How to Build Custom Q&A Transformer Models in Python
2021-02-12 13:30:03 UTC
https://youtu.be/ZIRmXkHp0-c
ZIRmXkHp0-c
UCv83tO5cePwHMt1952IVVHw
ZIRmXkHp0-c-t1017.76
So we have our context, and then we want to loop through the question answers.
1,017.76
1,033.2