Implementation of the "Self-Rewarding Language Models" Paper by MetaAI
In plain words
This is an open-source implementation of MetaAI's self-rewarding language models research, available on GitHub. It allows developers and researchers to explore a machine learning approach where language models generate their own reward signals during training. The implementation is designed for those interested in experimenting with advanced model training techniques and understanding how models can evaluate their own outputs to improve performance.
written from the facts on this page · September 2026
More life & fun this month
the category →- TL
Life & fun · 10d ago · louisabraham.github.io
Photosynthesis fires two of your iPhone
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Scroll through all 43,252,003,274,489,856,000 reachable Rubik's Cube permutations.
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Hi HN, I built Eigendrum, a web tool that solves the 2D wave equation for arbitrary shapes so you can hear what they sound like as drums. How it works: * Solves -∇²u = λu using finite element analysis (Kφ = λMφ) on a triangle mesh. * Validated to <0.1% error against closed-form solutions for circles (Bessel zeros) and rectangles. * Sound model factors in strike location, Rayleigh damping, and mallet width. * Includes Kac drums I & II to demonstrate identical sound spectra from different geometries. * No frameworks, build steps, or dependencies. Repo and tests:…
Life & fun · 26d ago · baselashraf81.github.io
Launched alongside, March 2024
the whole month →
- 3Y
Life & fun · 2024 · github.com
Microlaunch▲1,116Launch and get feedback on both the idea and product
Dev tools · 2024 · microlaunch.net
