stephanes-dev/ModelElohim
Can I trust it?
Worth a closer look before you use it.
Warnings Check
Very new: it was created 11 days ago. Wait a little before installing it.
Stars from real accounts No data
We haven't checked its stars for fakes yet.
Active OK
Last change 10 days ago.
Licence OK
MIT: you can use it for free, also in a commercial product. Keep the licence notice.
Quick checks from public data. They help, but they are no guarantee.
What it is
A distributed neural network engine described as built for real-time, auto-scalable machine learning computations on parallelized, data-intensive platforms. The README is mostly placeholder text and does not document its API, features or architecture.
Who it's for
Developers exploring distributed machine learning computations on parallelized platforms
How to use it
Install
pip install -r requirements.txtFrom its README. Check it there before running it.
Ask your AI to set it up
Paste this into Claude, ChatGPT or your coding assistant.
Help me install and set up stephanes-dev/ModelElohim in my project. Follow its README: https://github.com/stephanes-dev/ModelElohim. Explain each step and check it is safe before running anything.
Star curve
Get alerts for repos like this
We'll email you when something in Models & inference starts rising. Free, once a week, only what matches.
21,780 GitHub repos watched and ranked every hour. Figures as of 28 October 2026.
What arrives: one email on Mondays with the repos that match, never more. See last week's. Privacy
For maintainers
Add this badge to your README. It shows the repo's place on the radar, updates every hour and links back to this page.
[](https://repoalerts.com/repo/stephanes-dev/ModelElohim?ref=badge)Similar repos
- stephanes-dev/SuperficialChimera
A PHP project described as an engine for high-performance analytics on distributed data streams, with adaptive real-time processing and auto-scaling. The README is generic and contains no concrete API
- stephanes-dev/AbyssGriffin
Describes itself as a real-time, event-driven system for distributed processing, with auto-scaling across multiple processors under a unified manager. The README gives no further detail on features or
- Fryankarangora/RindBehemoth
A JavaScript project that describes itself as enabling distributed, real-time data processing and auto-scaling for concurrent task management on a centralized server. The README is largely repetitive
- flybrainlabs/miner
Native and WebAssembly simulation engines for deterministic integer leaky integrate-and-fire (LIF) networks, with browser workers, persistent model and result storage, and a three-stage mining workflo
- prabanta-dev/janas
A C inference engine for running large mixture-of-experts language models on ordinary computers, with or without a GPU. Weights stay on disk, and the experts each token needs are streamed from an NVMe
- iha2/superlite
A Claude Code plugin that plans a software build, splits it into tasks that run in parallel, assigns each task to a model by difficulty, checks the seams between parts and reviews the result. The user