YTBN-Graphing-Software
agi-pack
| YTBN-Graphing-Software | agi-pack | |
|---|---|---|
| 2 | 3 | |
| 7 | 15 | |
| - | - | |
| 7.2 | 8.1 | |
| 3 months ago | 4 months ago | |
| Rust | Python | |
| GNU Affero General Public License v3.0 | MIT License |
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.
YTBN-Graphing-Software
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Ask HN: Show me your half baked project
I wrote this cross-platform graphing software in Rust: https://github.com/Titaniumtown/YTBN-Graphing-Software
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What’s everyone working on this week (22/2022)?
Source Code (licensed under agplv3): https://github.com/Titaniumtown/YTBN-Graphing-Software
agi-pack
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AGI-pack: Dockerfile generator for ML developers
Here’s a fun project I hacked together this weekend.
https://github.com/spillai/agi-pack
TL;DR `agi-pack` is a Dockerfile generator for machine learning (ML) developers that is simple, hackable and extensible. Inspired by Replicate's cog, Baseten's truss, skaffold, and docker-compose services, I wanted a simple and standalone tool that could generate docker images given a simple YAML specification (i.e. python version, system packages, conda/pip dependencies, GPU libraries etc), without any added cruft/dependencies of vendors and services.
To get started, just run `pip install agi-pack` in your virtual env.
Check out the quickstart (https://github.com/spillai/agi-pack#quickstart-) section to see what `agi-pack` can do. If you’re interested in building multiple docker targets, the advanced section (https://github.com/spillai/agi-pack#more-complex-example-) might pique your interest.
Why the name? `agi-pack` is very much tongue-in-cheek -- we are soon going to be living in a world full of quasi-AGI agents orchestrated via ML containers. At the very least, `agi-pack` hopes to provide the building blocks for us to build a more modular, re-usable, and distribution-friendly container format for "AGI". ;)
Fun fact: More than 75% of the original implementation was generated by conversations with GPT-4 + Github Co-pilot.
Let me know what you think. Feel free to reach out / DM if you’d like to build on this work, happy to chat and hear about your use-case. DMs open on Twitter (https://twitter.com/sudeeppillai).
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Ask HN: Show me your half baked project
Here’s a fun project I hacked together last weekend — https://github.com/spillai/agi-pack
TL;DR agi-pack is a Dockerfile generator for machine learning (ML) developers that is simple, hackable and extensible.
What are some alternatives?
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