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

[primordialsoup]

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

[brookst]

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.

[avereveard]

yeah as usual these model can barely sustain a conversation and fall apart the moment actual instructions are given. typical prompt they fail to udnerstand:

"what is pistacchio? explain the question, not the answer."

all these toy llm: "pistacchio is..."

gpt is the only one that consistently understand these instructions: "The question "what is pistachio?" is asking for an explanation or description of the food item..."

this makes these llm basically useless for obtaining anything but hallucinated data.

[TwoFactor]

Thats an interesting test. Here's what I got from ChatGPT:

---GPT-3.5---

Here are some words that end in "agi":

Strategy

Swarajya

Arthroplasty

Sialagogue

Podagric

Gynecology

Physiognomy

Ophthalmology

Esophagitis

Otalgia

--- GPT-4 ---

Here are some words that end in "agi":

Swaggy

Raggi

Magi

Gagi

Stagi

Please note that some of these words may not be commonly used or may be specific to certain dialects or regions.

[sharonzhou]

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

[jeffybefffy519]

Im confused, what are you actually offering? Does my fine tuning data get shared with your platform’? Does the model get fine tuned on your end or my own system? Do you host the model?

[jasonjmcghee]

You’re building some seriously exciting stuff! Looking forward to diving in.

[ec109685]

This headline is totally editorializing. Stick with the source one. “Introducing Lamini, the LLM Engine for Rapidly Customizing Models”

So much click bait in the LLM space.

[mkl]

Is it still editorialising when OP is the CEO of the company?

[iguana]

Trivial examples show that this isn't nearly as good as ChatGPT. The headline should be changed.

[mensetmanusman]

It took Open.ai 10 years of fine tuning, can’t expect things to work as well in day 1.

[furyofantares]

The actual post doesn't say "as Good as ChatGPT", why does the HN title?

I don't really care to click on something I know is obviously lying to me.

[batch12]

I've been playing a bit with stacking transformer adapters to add knowledge to models and so far it has met my needs. It doesn't have the same illusion of intelligence, but so far it's just as good as a multitasking intern, so I am still having fun with it. I wonder if this is basically doing the same thing.

[leobg]

Interesting. Do you know if this can be done with Sentence Transformers, too? Picking a good performing one from HF. Then training an adapter for the domain (unsupervised). Then adding another one using actual training triplets (base, similar, non-similar)?

[eschluntz]

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

[gdiamos]

Free open source libraries.

Paid LLM hosting. 50% cheaper than OpenAI, pay per compute needed to run & create the LLM. Export the weights anytime you want.

Enterprise VPC deployments.

[atulika612]

If I want to export the model and run it myself, can I do that?

[mise_en_place]

Why wouldn’t we use something like DeepSpeed? It’s a one-click on Azure. What’s the value add?

[cultofmetatron]

I hope this turns out be as good as chatgpt and not "we have chatgpt at home"

[acapybara]

Try SuperCOT 30B.

[digitcatphd]

GPT at this point is more than an LLM, it is a baseline layer of logic using the underlying transformer technology. This will be challenging to replicate without the same size of data sets

[gdiamos]

Noting that the Github repo includes a data pipeline for instruction fine tunining.

What's the difference between this and other data pipelines like Alpaca?

[verdverm]

Aren't you Greg Diamos, the founder, why are you asking this instead of answering?

[8thcross]

looks great...looking forward to trying it out