Super excited to see improvement in NER accuracy in SpaCy 3.0.
SpaCy 3.0
41–50 of 82 posts
Re: SpaCy 3.0
#42Earlier quoted context omitted.
The author of FastAPI https://twitter.com/tiangolo is a Spacy employee
Yep, that's me, I work at Explosion (spaCy's home)!
Big fan my dude! While FastAPI is amazing, the docs for it are a work of art. I know a few people that have just used the FastAPI docs to learn what API's are and how they work, nevermind how use FastAPI itself.
Re: SpaCy 3.0
#43Earlier quoted context omitted.
As someone who never used NLP, what is it used for? Or better what is SpaCy used for - I know that it can generate Texts... but how would I use it in a business?
Obviously, it depends, but assuming you do have an NLP use case already, there are certain things that you will almost certainly have to do in your preprocessing regardless of your task. For example, sentence parsing. Writing your own basic sentence parser is fairly easy. Writing your own _good_ sentence parser is a nightmare akin to trying to parse HTML with regex. SpaCy provides a very good one for you. Down the li…
Thanks for the explanation. Guss I never had an NLP usecase.
So SpaCy can take a text or sentences apart and knows what the parts "mean" but I can't think of a problem to solve with this.
Maybe summarize a text or something, but I guess I am not imaginative enough
Re: SpaCy 3.0
#44Earlier quoted context omitted.
Yep, that's me, I work at Explosion (spaCy's home)!
Big fan my dude! While FastAPI is amazing, the docs for it are a work of art. I know a few people that have just used the FastAPI docs to learn what API's are and how they work, nevermind how use FastAPI itself.
Thanks for saying that! :)
Re: SpaCy 3.0
#45I have been using Spacy3 nightly for a while now. This is game changing. Spacy3 practically covers 90% of NLP use-cases with near SOTA performance. The only reason to not use it would be if you are literally pushing the boundaries of NLP or building something super specialized. Hugging Face and Spacy (also Pytorch, but duh) are saving millions of dollars in man hours for companies around the world. They've been a rev…
Everything in the above paragraph sounds like a hyped overstatement. None of it is. As someone that's worked on some rather intensive NLP implementations, Spacy 3.0 and HuggingFace both represent the culmination of a technological leap in NLP that started a few years ago with the advent of transfer learning in NLP. The level of accessibility to the masses these libraries offer is game-changing and democratizing.
Can you help, please?
I want to use AI to translate (localize) messages for free software, in my case, Ukrainian language. My plan to improve quality of automated translation is to translate from similar languages in parallel, i.e. give a same message in English, Russian, Polish, and expect message in Ukrainian as output.
Where I should start? Which libraries to use? How to connect them? How to train them?
Re: SpaCy 3.0
#46I have been using Spacy3 nightly for a while now. This is game changing. Spacy3 practically covers 90% of NLP use-cases with near SOTA performance. The only reason to not use it would be if you are literally pushing the boundaries of NLP or building something super specialized. Hugging Face and Spacy (also Pytorch, but duh) are saving millions of dollars in man hours for companies around the world. They've been a rev…
Everything in the above paragraph sounds like a hyped overstatement. None of it is. As someone that's worked on some rather intensive NLP implementations, Spacy 3.0 and HuggingFace both represent the culmination of a technological leap in NLP that started a few years ago with the advent of transfer learning in NLP. The level of accessibility to the masses these libraries offer is game-changing and democratizing.
i am curious, what kind of project are you working on?
Re: SpaCy 3.0
#47I stumbled over SpaCy when looking for something to extract key words and numbers from sentences, however it looked a bit daunting and/or overkill. Think recipes or similar, turning "take three tablespoons of sugar" into [3, 'tablespoons', 'sugar'] or similar. Should I give it another shot or are there libraries more suited for this than just plain regexp galore?
I did that years ago for some project. For recipes you can probably get away with regular expressions.
But with Spacy you could tokenize the sentence, then tag each work with the Part of Speech it is, and then find patterns eg. Verb Number Noun Preposition Noun
Then match the first noum against a list of measurements (tablespoon, teaspoon, tbsp...) and extract the rest of the components.
Re: SpaCy 3.0
#48Thanks to the SpaCy team! I spent a lot of time over about 20 years working on my own NLP tools. I stopped doing that and mostly now just use SpaCy (and sometimes Huggingface and Apple’s NLP models).
Have you compared SpaCy with Apple's NLP on M1? I presume GPU is not being used by SpaCy on M1.
I have used both on M1, but compared them.
Re: SpaCy 3.0
#49Earlier quoted context omitted.
Everything in the above paragraph sounds like a hyped overstatement. None of it is. As someone that's worked on some rather intensive NLP implementations, Spacy 3.0 and HuggingFace both represent the culmination of a technological leap in NLP that started a few years ago with the advent of transfer learning in NLP. The level of accessibility to the masses these libraries offer is game-changing and democratizing.
Can you help, please? I want to use AI to translate (localize) messages for free software, in my case, Ukrainian language. My plan to improve quality of automated translation is to translate from similar languages in parallel, i.e. give a same message in English, Russian, Polish, and expect message in Ukrainian as output. Where I should start? Which libraries to use? How to connect them? How to train them?
I've been using LASER from Facebook Research via https://github.com/yannvgn/laserembeddings to accept multi-lingual input in front of the the domain-specific models for recommendations and stuff (that are trained on English annotated examples).
Re: SpaCy 3.0
#50I'll add my hats off to to @ines and the spaCy team. It's super impressive. There's also a (free) orientation course I'd recommend at https://course.spacy.io/