The website states it's using the "langcss.fast" model, which made me think it's a custom-trained model. But if you can just easily switch between Groq and OpenAI, that makes it seem like there's no fine-tuning happening. Could you shed some light on this?
I like the website and my first prompt to create a modern table worked reasonably well, but if it's just a re-skinned ChatGPT, I probably wouldn't wanna spend extra money on it.
shouldn't your willingness to pay/not pay be a function of your experience and the value the product delivers you, rather than an implementation detail such as fine tuning vs prompt engineering?
I think this difference should be comparable to asking something like:
This website uses UsersDb, which makes me think you have built a custom database, but if you can easily switch between sqlite and postgres, that makes it seem like there's no real work happening. Could you shed some light on this?
I feel this comparison is almost entirely valid since fine tuning can be as simple as:
- Create request/response tabular data
- Click "upload" on leading LLM provider
- Click "fine tune"
- Change your code to reference llm.com/finetuned instead of llm.com/base-model
> shouldn't your willingness to pay/not pay be a function of your experience and the value the product delivers you, rather than an implementation detail such as fine tuning vs prompt engineering?
bullshitting/lying isn’t implementation detail, it’s a mindset and I understand people who actively try to avoid it. Prompts and rag don’t make it a new powerful model that is superior to say ChatGPT
Yeah, that's basically what I was thinking. I didn't wanna use the word "lying" as to not appear super confrontational, but when someone claims it's using a model called "langcss.fast", it should be safe to assume that they're actually using a custom model. It's disingenuous at best.
I'm not even saying there is any need for a custom model. Obviously, RAG etc. can work just as well, or even just a well-crafted prompt on a foundation model. But selling it as a custom model is misleading on purpose, and deters me from using the product.
Of course, a well-crafted prompt and RAG or other means of retrieving relevant information can work very well.
The reason why I was asking is that as a potential customer, I kinda feel cheated reading about a langcss.fast model that doesn't actually exist. I don't think there's any need for putting this misleading (well, actually not even misleading; just plain wrong) information on the website, to make potential customers think you've trained a custom model on tailwind etc.
Honesty is a very attractive selling point, at least to me, and I'd bet it is to others too.
Ah I see. The idea behind the model name is to kind of abstract away so the user needs to think less (why was it Llama last week and now it is Mixtral).
I have updated the UI to make it more obvious what the model is.
I am happy for people to know how the sausage is made and go direct to that provider if they don't see value in the UI. I might write an architecture post one day too.
