I've included plenty of new subtitles from just after 2021-2022 that I've found in the RUNBKK packs and scraped for all their subs. Merged it absolutely was most likely greater than 5000 new ones I've additional but I have hardly ever checked what the precise number was.
A: Of course, I imagine that is a superb use of this thread. Exhibiting off the process and what will get superior success is helpful.
initial_prompt: You are able to enter a sentence or number of phrases like a string to try to bias the interpretation in a way. It's not at all clear whether This is often designed to applay to only the primary phase or the whole transcript, but in long run versions it will probably be a tad extra obvious or adaptable.
There's logit biasing or extra instruction facts as is possible alternatives, but I have not built Substantially perception of it.
Owing to ding73ding. Even though her/his? subtitle file was a Chinese translation, I found an English device translation on SubtitleCat but I would not have seemed had ding73ding not posted it. I cleaned the device translation up a tad and tried out to higher interpret what was remaining reported, but otherwise didn't intentionally twist the storyline.
Any person know how to find their sub in srt or text file or willing to share? I don't know Chinese, so it's hard to find subs in text file Despite having the assistance of google translator Click on to increase...
bosco50 mentioned: So I started employing Whisper to translate subtitles and it is taking an exceptionally while, Virtually 3 hrs to translate just one Film. Does it always choose this long? I used to use DeepL and translate line by line and it was quicker. Am I performing anything Mistaken? Click to broaden...
I will update this write-up and the FAQ based on feedback and dialogue. Superior to acquire an early Model of this out than to sit on it right until I hardly ever great it.
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one. The subs within the pack are generally Chinese, so I thought I will hold it the identical Along with the pack. two. I can read through both of those Chinese and English, but I think machine translation is a lot more accurate for Chinese.
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⦁ Whisper is negative at "chatting filthy". You will discover most likely tips on how to resolve this, but it's not hard to see why the education data sets may well veer clear of filthy language.