[HN Gopher] Launch Lamini: The LLM Engine for Rapidly Customizin...
       ___________________________________________________________________
        
       Launch Lamini: The LLM Engine for Rapidly Customizing Models as
       Good as ChatGPT
        
       Author : sharonzhou
       Score  : 61 points
       Date   : 2023-04-28 16:35 UTC (6 hours ago)
        
 (HTM) web link (lamini.ai)
 (TXT) w3m dump (lamini.ai)
        
       | [deleted]
        
       | gdiamos wrote:
       | 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 wrote:
         | Aren't you Greg Diamos, the founder, why are you asking this
         | instead of answering?
        
       | eschluntz wrote:
       | Very exciting! Glad to finally be able to get beyond prompt
       | engineering. What's the pricing model like?
        
         | gdiamos wrote:
         | 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.
        
           | ec109685 wrote:
           | 50% cheaper than OpenAI compared to what?
        
             | verdverm wrote:
             | OpenAI models have wide ranges in prices, so indeed some
             | clarity is needed
        
       | atulika612 wrote:
       | If I want to export the model and run it myself, can I do that?
        
       | primordialsoup wrote:
       | 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
        
         | avereveard wrote:
         | 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.
        
         | brookst wrote:
         | 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.
        
           | ksaj wrote:
           | You can't ask ChatGPT to count something and expect that it
           | can answer correctly, because it does not have counting
           | logic. It is a language model, not a math model. People use
           | this to "prove" hallucinations, but when you ask it something
           | that is within it's programmed abilities, you get something
           | at least close to what you want.
           | 
           | Having said that, here are the words ChatGPT gave me for the
           | same prompt:
           | 
           | Magi Nagi Sagi Yagi Adagi Galagi Tegagi Sigikagi Tagi Wagagi
           | 
           | It missed Unagi, surprisingly. But it is still leagues ahead
           | of the point brought up here.
        
           | mckirk wrote:
           | The problem is that these models do not have any working
           | memory they could use to carry out such tasks, which are on a
           | meta-level when seen from a language perspective. They can
           | only go with their 'gut instinct' for selecting the next
           | word, they can't 'consider and ponder the problem internally'
           | first.
        
             | sp332 wrote:
             | The problem is that the input is tokenized before the model
             | gets it as input. It does not see the individual letters
             | "t" + "o". It gets one single token, #1462. The word "toe"
             | is another single token, #44579. Maybe over time it could
             | learn from context that inputs that start with #44579 also
             | satisfy the constraint of starting with #1462, but that's a
             | lot of work and it's not going to happen for all
             | combinations of letters.
        
             | jameslevy wrote:
             | Perhaps prompting the model to first describe its approach
             | to answering the question. This type of chain-of-thought
             | technique can yield better results.
        
           | chaxor wrote:
           | It's not a character based model (likely - although it's
           | closed source so anything is technically possible behind the
           | scenes) so this makes some sense. The system can infer some
           | relationships, which may be why 'agy' is conflated with 'agi'
           | interestingly, but the tokenization process yields sequences
           | of 'symbols' or indexes that are decided to English - so the
           | system has a more difficult task when asked about 'e's
           | (probably something like token 4893) and has to determine
           | which tokens (e.g. [358,284840, 58292, 4830104, 57282,
           | 4829193, 58282, 384, 24945] contain 'e's or token 4893). None
           | of them do directly it seems - but 58292 may be 'ee' - so you
           | would get this wrong as well.
        
         | TwoFactor wrote:
         | 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.
        
           | armchairhacker wrote:
           | Stagi isn't a word (unless you count Lojban). Gagi isn't a
           | word unless you could Filipino slang.
        
             | mejutoco wrote:
             | To be fair the question did not specify the language and
             | included a disclaimer about it.
        
       | ec109685 wrote:
       | 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.
        
       | sharonzhou wrote:
       | 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 wrote:
         | 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 wrote:
         | You're building some seriously exciting stuff! Looking forward
         | to diving in.
        
       | furyofantares wrote:
       | 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.
        
       | iguana wrote:
       | Trivial examples show that this isn't nearly as good as ChatGPT.
       | The headline should be changed.
        
       ___________________________________________________________________
       (page generated 2023-04-28 23:01 UTC)