skweak VS sqlmodel

Thanks for pointing me in the right direction. Seems like there’s a few other approaches with weak supervision: https://github.com/NorskRegnesentral/skweak

Code for https://arxiv.org/abs/2104.09683 found: https://github.com/NorskRegnesentral/skweak

Hi Raza here, one of the other co-founders.

I know that HN likes to nerd out over technical details so thought I’d share a bit more on how we aggregate the noisy labels to clean them up.

At the moment we use the great Skweak [1] open source library to do this. Skweak uses an HMM to infer the most likely unobserved label given the evidence of the votes from each of the labelling functions.

This whole strategy of first training a label model and then training a neural net was pioneered by Snorkel. We’ve used this approach for now but we actually think there are big opportunities for improvement.

We’re working on an end-to-end approach that de-noises the labelling function and trains the model at the same time. So far we’ve seen improvements on the standard benchmarks [2] and are planning to submit to Neurips.

R

[1]: Skweak package: https://github.com/NorskRegnesentral/skweak

skweak.

For more advanced unsupervised labeling, you should check skweak

I'm the main developer behind skweak by the way, happy to hear you're interested in our toolkit :-) We do already have a small list of products (see https://github.com/NorskRegnesentral/skweak/blob/main/data/products.json) extracted from DBPedia and Wikidata, but it may not be exactly the type of products you're looking for.

Seems like this is a known bug in SQLModel: https://github.com/tiangolo/sqlmodel/issues/10

I have not used it myself but the creator of fastapi has made https://github.com/tiangolo/sqlmodel

I have already posted this question in Stack Overflow and GitHub and have been ignored in both 😢. You guys are my last hope.

I had a requirement to process and validate large payloads of JSON concurrently for a web service, initially I implemented it using jsonschema and fastjsonschema but I found the whole JSON Schema Specification to be confusing at times and on top of that wanted better performance. Albeit there are ways to compile/cache the schema, I wanted to move away from the schema specification so I wrote a validation library inspired by the design of tiangolo/sqlmodel (type hints) to solve this problem easier.

Github Repository

I would say as long as your current solution works and is easy to maintain keep it. If you want to switch I would recommend FastAPI, it is new(ish), but definitely old enough to have been tested and used in a large variety of production usecases. In your case it might be interesting to have a look at SQLModel (works with FastAPI, same author), especially if the API endpoints match closely to the database objects. https://github.com/tiangolo/sqlmodel

SQLModel.

Sounds similar to https://github.com/tiangolo/sqlmodel

There was a lot of hype and excitement around the release of SQLModel, a Pydantic + SQLAlchemy hybrid Model library with native integration for FastAPI. I pulled it out just now and there hasn't been any update beyond the initial anouncment on August 25th.