Launch Lamini: The LLM Engine for Rapidly Customizing Models as Good as ChatGPT

Hi HN!

I’m super excited to announce Lamini, the LLM engine that gives every developer the superpowers that took the world from GPT-3 to ChatGPT!

I’ve seen a lot of developers get stuck after prompt-tuning for a couple days or after fine-tuning an LLM and it just gets worse—there’s no good way to debug it. I have a PhD in AI from Stanford, and don’t think anyone should need one to build an LLM as good as ChatGPT. A world full of LLMs as different & diverse as people would be even more creative, productive, and inspiring.

That’s why I’m building Lamini, the LLM engine for developers to rapidly customize models from amazing foundation models from a ton of institutions: OpenAI, EleutherAI, Cerebras, Databricks, HuggingFace, Meta, and more.

Here’s our blog announcing us and a few special open-source features! https://lamini.ai/blog/introducing-lamini

Here’s what Lamini does for you: Your LLM outperforms general-purpose models on your specific use case You own the model, weights and all, not us (if foundation model allows it, of course!) Your data helps the LLM, and build you an AI moat Any developer can do it today in just a few lines of code Commercial-use-friendly with a CC-BY license

We’re also releasing several tools on Github: 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

Very exciting! Glad to finally be able to get beyond prompt engineering. What's the pricing model like?

Congrats! I went to your demo and asked for words that end in agi. This is what I got:

--

agi, agi, agi, agi, agi, agi, agi

These are some of the words that end in agi. You can also use the word agi in a sentence. For example, "I am going to the grocery store to get some agi."

These are some of words that end in agi.

These are some words that end in agi.

maximize, maximize, maximize, maximize, maximize, maximize, maximize, maximize

These are some words that ends in agi

--

So I think this needs more work to get to "as good as ChatGPT". But having said that, congrats on the landing

It's a fair criticism, and ChatGPT does better, but this isn't a great test of model quality. All LLMS that rely on tokenization struggle with being introspective on language. Try asking chatGPT to count how many e's are in a sentence, or to list all words that start with "to" and end wide "de".

I haven't heard anyone describe the phenomenon clearly, but I expect it is a challenge with reasoning over both intent of the prompt and specific token IDs.