OpenFilter VS hyperlearn

Compare OpenFilter vs hyperlearn and see what are their differences.

OpenFilter

This repository refers to the paper currently under review for the 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks, under the title "OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters", by Piera Riccio, Bill Psomas, Francesco Galati, Francisco Escolano, Thomas Hofmann and Nuria Oliver. (by ellisalicante)
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OpenFilter hyperlearn
1 4
5 1,578
- 4.3%
0.8 0.0
about 1 year ago almost 2 years ago
Jupyter Notebook Jupyter Notebook
- Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

OpenFilter

Posts with mentions or reviews of OpenFilter. We have used some of these posts to build our list of alternatives and similar projects.
  • [P] Trying to create Ar Filter
    1 project | /r/MachineLearning | 12 Mar 2023
    Im trying to create a Ar Filter using FairFace( https://www.kaggle.com/datasets/aibloy/fairface) dataset. I couldnt find anything useful to implement. OpenFilter(https://github.com/ellisalicante/OpenFilter) is one of the things done before but i coulnt find to implement with a model. Does anyone know where should i start with ?

hyperlearn

Posts with mentions or reviews of hyperlearn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-01.
  • 80% faster, 50% less memory, 0% accuracy loss Llama finetuning
    3 projects | news.ycombinator.com | 1 Dec 2023
    I agree fully - what do you suggest then? OSS the entire code base and using AGPL3? I tried that with https://github.com/danielhanchen/hyperlearn to no avail - we couldn't even monetize it at all, so I just OSSed everything.

    I listed all the research articles and methods in Hyperlearn which in the end were gobbled up by other packages.

    We still have to cover life expenses and stuff sadly as a startup.

    Do you have any suggestions how we could go about this? We thought maybe an actual training / inference platform, and not even OSSing any code, but we decided against this, so we OSSed some code.

    Ay suggestions are welcome!

  • 80% faster, 50% less memory, 0% loss of accuracy Llama finetuning
    6 projects | news.ycombinator.com | 1 Dec 2023
    Good point - the main issue is we encountered this exact issue with our old package Hyperlearn (https://github.com/danielhanchen/hyperlearn).

    I OSSed all the code to the community - I'm actually an extremely open person and I love contributing to the OSS community.

    The issue was the package got gobbled up by other startups and big tech companies with no credit - I didn't want any cash from it, but it stung and hurt really bad hearing other startups and companies claim it was them who made it faster, whilst it was actually my work. It hurt really bad - as an OSS person, I don't want money, but just some recognition for the work.

    I also used to accept and help everyone with their writing their startup's software, but I never got paid or even any thanks - sadly I didn't expect the world to be such a hostile place.

    So after a sad awakening, I decided with my brother instead of OSSing everything, we would first OSS something which is still very good - 5X faster training is already very reasonable.

    I'm all open to other suggestions on how we should approach this though! There are no evil intentions - in fact I insisted we OSS EVERYTHING even the 30x faster algos, but after a level headed discussion with my brother - we still have to pay life expenses no?

    If you have other ways we can go about this - I'm all ears!! We're literally making stuff up as we go along!

  • [Project] BFLOAT16 on ALL hardware (>= 2009), up to 2000x faster ML algos, 50% less RAM usage for all old/new hardware - Hyperlearn Reborn.
    2 projects | /r/MachineLearning | 2 Jun 2022
    Hello everyone!! It's been a while!! Years back I released Hyperlearn https://github.com/danielhanchen/hyperlearn. It has 1.2K Github stars, where I made tonnes of algos faster:

What are some alternatives?

When comparing OpenFilter and hyperlearn you can also consider the following projects:

goodreads - code samples for the goodreads datasets

gpt-fast - Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.

awesome-data-centric-ai - Open-Source Software, Tutorials, and Research on Data-Centric AI 🤖

notebooks - Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.

google-research - Google Research

data-science-notes - Notes of IBM Data Science Professional Certificate Courses on Coursera

image-crop-analysis - Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

ocaml-torch - OCaml bindings for PyTorch

datasets - 🎁 5,400,000+ Unsplash images made available for research and machine learning

DiffSharp - DiffSharp: Differentiable Functional Programming

MegEngine - MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架

python-machine-learning-book - The "Python Machine Learning (1st edition)" book code repository and info resource