Negative example: I was looking into the German manual of my Canon EOS R5 II, and it is just fluff. Hundreds of pages, full of white space, telling me about features without actually explaining what they mean. Awful automatic translations. Their manuals used to be good (looking at my EOS 6D). But these days: oh boy.
At that moment I felt sorry for this company, very sorry. How can you have so much disrespect for your customers? Does anyone in the physical world talk like this or do you marketing guys want to be talked to in such terms?
Brutal.
I also wrote on what I think makes docs beautiful, by the way! https://passo.uno/what-makes-docs-beautiful/
But if you look how much manuals get ignored by the customer, it doesn’t make sense to put work into them.
It is much better to let a YouTuber do it, by lending them the product and throw small amount of money against them.
Manuals are just there for legal or certifications requirements these days.
When was the last time you met a good technical writer? It’s a vanishing profession.
I'd really like to see the Win2K-style docs on REST, for example.
Edit: it was right there, in bold, too. https://gist.github.com/theletterf/0b8ee1112fbd087f3141d0cad...
Is that why though? You need a beast of a machine to run a functional local model in my experience.
I think the big part is there’s significant sticker shock to buying capable hardware.
That said,
> weekend. I chose to try fine-tuning on two models, Llama 3.1 8B Instruct and Qwen 2.5 7B Instruct. At their size (around 8B) they run comfortably on a MacBook Air
Perhaps I spoke too soon?
Anyway
> I chose the Microsoft collection as the source of training materials. The collection contains out-of-print docs published between 1977 and 2005: more than 37 million words, covering old systems and SDKs
this strikes me as a very specific brand of 1995’s prose, spanning about 30 years. It’s a cool article though, so maybe that’s a forgivably clickbaity title.
Obviously not the largest, up-to-date models but for what I expect most people use them for, even on hn, there are some shockingly good models that dont require €4k machines.
I have a desktop with an AMD 6900XT and 5600 with 32GB ram. Obviously no slouch but its several years old at this point. I can comfortably run qwen 3.5 9b and get a speedy 60 token/sec output with decent results.
Is there some secret I’m missing? I’ve tried rolling my own harness, and tried a few of the ones the cool kids use - I think pi was the most recent. Not quite my tempo, I’m afraid.
The easiest way I have found is to use LM Studio, grab the model you want, and point whatever tooling you're using at the local exposed API.
You will have to configure the model params (temperature, etc) a bit to get the style you're expecting but it works decently well for me.
It's probably a fair approach to say the significant influence (training dataset) on writing at a particular time is the preceeding 30 years' material? It's certainly not only what's already written that year (nor anything since).
https://github.com/space-bacon/SRT
The HF zool4nd3r demo may be useful
Also your documents use a ton of nonstandard jargon which only serve to confuse laypeople and annoy anyone who is familiar with ML. Saying your change adds “semiotic awareness” is meaningless when your experiments claim only marginal improvements. Clearly the model had most of the capability before.
More generally, who is it for? People who have expertise in ML are not going to take it seriously. People who don’t?
Also to say that a philosopher that died 100 years ago inspired a new attention head is another instance of GPT off his rocker again. You don’t need MAH to contextualize “freedom” in a sentence. Attention already does that.
Edit: its not GPT nor off rocker. This repo empirically proved computational semiotics with the reference to C.S. Peirce, Paul Kockelman, and many other respected contemporary semioticians.
The technical implementation details are also useful to have, but they're a bit hard to parse into "what is this?"
they need specific coaching to get them to try to write for the perspective of a new user
Also is SRT really suitable for style transfer?
I mean this seems to be another network overlaid on top of the LLM steering it, but it needs some target to determine whether the underlying LLM drifted away from it
Am I the only one feeling this way?
There's just so much shitty technical documentation out in the world.
Is there anything else you'd like to ask me?
The other case is when I - gasp - do something myself, and the docs are actually reasonable / easy to reference. There are workflows where me doing the thing is just plain faster still, even when including hitting up the docs real quick.