Thinc v8 will also be powering the upcoming @spacy_io v3 and make it easy to integrate your own custom models. We're especially excited about the config system and static type checking features.
Config: https://thinc.ai/docs/usage-config …
Types:https://thinc.ai/docs/usage-type-checking …
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Intro notebook on @GoogleColab: Composing and training a model on the MNIST data, using config files, registering custom functions and wrapping PyTorch, TensorFlow & MXNet modelshttps://colab.research.google.com/github/explosion/thinc/blob/master/examples/00_intro_to_thinc.ipynb …Prikaži ovu nit
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This looks great! :)
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I think this is a really great design and engineering effort! Looks really cool! Use-case wise, I am not quite sure what to do with it. I.e., why does an API have to support several other frameworks (what's the advantage for the user?) 1/...
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oh my god, im very excited to try this
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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I've also been a fan of thinc-ing.
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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As always, gorgeously beautiful documentation too - very easy on the eyes!!

(My only gripe with the logo is that the 'C' kinda looks like a 'G')Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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This is really nice! If I used it in Ludwig instead of the TensorFlow backend I would have static type checking that I was considering implementing myself. Great stuff!
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Huh, why is it ReLu and not ReLU?
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Uuuh no good reason. I should fix that thanks! For some reason I always wrote ReLu? Maybe i'll just make it Relu.
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Čini se da učitavanje traje već neko vrijeme.
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Static type checking
Mix
Integrated config system
Extensible backends incl. JAX (experimental)
Variable-length sequences & more