Hi! Great video, very helpful! I'm wondering why `model.transform(data)` function always takes 1-2 seconds to run, but `result.show()` takes many minutes(depending on the size of input text) and says `WARN DAGScheduler: Broadcasting large task binary with size 1886.0 KiB`. At the same time light.annotate("text...") also takes a lot of time to run Does `model.transform(data)` really apply the forward propagation and transform the input text? Because I can't get the readable result without invoking either show() or .toPandas() functions, which take minutes to run
Hey thanks for the great introduction! Is there a simple way to replace the identified named entities in a given sentence with their respective NER Tag?
Awesome video, super clear. Love it
Hi! Great video, very helpful!
I'm wondering why `model.transform(data)` function always takes 1-2 seconds to run, but `result.show()` takes many minutes(depending on the size of input text) and says `WARN DAGScheduler: Broadcasting large task binary with size 1886.0 KiB`.
At the same time light.annotate("text...") also takes a lot of time to run
Does `model.transform(data)` really apply the forward propagation and transform the input text? Because I can't get the readable result without invoking either show() or .toPandas() functions, which take minutes to run
Thanks for such a Nicely explained the video 👏.
Hey thanks for the great introduction! Is there a simple way to replace the identified named entities in a given sentence with their respective NER Tag?
Awesome video...will be gud if u can share the code as well