
I'm building an open, crowdsourced database of ML models - bsima
https://docs.google.com/spreadsheets/d/1ehKtQeuZKnE9R0JUFuRsV6B82p9KYkLKF7cMA7nH2cA/edit?usp=sharing
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ipsum2
PyTorch has PyTorch hub, a nicely formatted list of ML models:
[https://pytorch.org/hub/](https://pytorch.org/hub/)

Also, PapersWithCode
([https://paperswithcode.com/](https://paperswithcode.com/)) has leaderboards
and code :) most of the time with a pre-trained model.

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colincooke
This is great to see, I've seen lots of other lists on the web but always
happy for more (perhaps this will keep up to date).

I'd suggest adding a publication date column (should be easy to scrape if need
be). One thing I'm usually looking at as an ML researcher is recency, not
always a good proxy for quality but I'd much rather take a classification
model from 2019 than 2014 for example.

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bsima
Good idea, I'll add a pubdate column now

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alexellisuk
/subscribe

We've packaged a number of models in OpenFaaS and publish the containers in
our function store. You can check for nudes, colorise images, do OCR and
ImageNet is also available (called inception). I'd welcome contributions,
Tensorflow models are very easy to serve.

[https://github.com/openfaas/store](https://github.com/openfaas/store)

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franga2000
Thanks for pointing me at OpenFaaS! I've been working on packaging a bunch of
tedious things (facial recognition, filling PDF forms, file conversion, etc.)
into self-contained Docker containers with REST endpoints for use with my
projects and it never occurred to me that I was basically implementing FaaS.
Now I know where to find more (and eventually submit some of mine if they're
missing).

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RocketSyntax
I've heard this termed a Model Zoo.
[https://modelzoo.co/](https://modelzoo.co/)

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cyorir
And it's not the only one!

modelzoo.co is good for finding the best/most-used models but remains far from
being a complete zoo and lacks a sufficient list of models for certain tasks.

For a while I liked the GAN Zoo which was specifically for GANs, but I guess
there got to be too many GANs so it is no longer maintained.

[https://github.com/hindupuravinash/the-gan-
zoo](https://github.com/hindupuravinash/the-gan-zoo)

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bsima
I like the approach that ONNX is taking by standardizing the format. Hopefully
having a standard format also leads to having a central place or way to find
all of these models...

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hprotagonist
unfortunately model conversion isn’t lossless.

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akerro
[http://resources.wolframcloud.com/NeuralNetRepository](http://resources.wolframcloud.com/NeuralNetRepository)

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troysk
Have you thought of adding github like features like `forking` and `cloning`?
I have been thinking on those lines. Eg. One could fork the resnet model and
then transfer learn it to make it ecommerce apparel specific or self driving
specific.

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gardenfelder
perhaps an alternative would be to start a "models" section here?
[https://github.com/josephmisiti/awesome-machine-
learning](https://github.com/josephmisiti/awesome-machine-learning)

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isaaafc
Great idea, hope that will lead to more practical usage of deep learning. Any
plans of building one for datasets as well? Something like Kaggle's
collection, but used in research papers.

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jordiburgos
I thought that models are very dependent of the input data structure. Maybe
not the case for images

But what about the others? How this problem is solved ?

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RocketSyntax
You just re-fit the model on different data. It's called transfer learning.
The theory is that it will run with similar features in your input data,
therefore the weights will not need to be adjusted too much. You can also
freeze the weights of entire layers.

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LegitShady
That I have to log into Google docs to see. Why did you out google in front of
your open list?

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TACIXAT
I have no problem viewing it in an incognito window (not signed in). Perhaps
the settings have been changed?

