lamini VS cobalt-lang

Github Repo: https://github.com/lamini-ai/lamini

The data pipeline here https://github.com/lamini-ai/lamini uses a seed dataset from self-instruct (Apache 2 license), and edited models from Pythia (Apache 2) and Dolly (Apache 2). We release our code and data under a CC-BY 4.0 license.

Today, you can try out our hosted data generator for training your own LLMs, weights and all, without spinning up any GPUs, in just a few lines of code from the Lamini library. https://github.com/lamini-ai/lamini/

You can play with an open-source LLM, trained on generated data using Lamini. https://huggingface.co/spaces/lamini/instruct-playground

Sign up for early access to the training module that took the generated data and trained it into this LLM, including enterprise features like virtual private cloud (VPC) deployments. https://lamini.ai/contact

example: https://github.com/lamini-ai/lamini

Do you have an idea of what kind of language you'd like to work on? Are you more interested in a compiler or interpreter? What language do you want said compiler or interpreter to be written in? These are questions that will drastically shape your experience. For example, I tried writing interpreters a few times and hated it, but now I'm working on a computer and it's great (not to say that there's anything wrong with interpreters; it's a personal preference). And finally, I could use some help with my project, Cobalt (https://github.com/matt-cornell/cobalt-lang). It's a compiled language similar to C++ and Rust with the compiler written in Rust, and I'd be grateful for some help if you're interested.