mmis1000

For my personal experience, antropic model have better user experience except for 4.7 and 4.8 though. 4.7 and 4.8 feels like expensive downgrade of 4.6 to me (I didn't know why these two should even exist)

However it's less willing to obey your instruction so it's less usable for general runtine flows.

Although the underlying model is unknown. If it expose input token count, the tokenizer may be probable though. Most tokenizer segemnts wildly different in CJK inputs. It can probably be used to fingerprint the tokenizer based on token count if it is using existing tokenizer.

The way jev actually internally work could be interesting though. I believe most llm are only tuned to return the first or second logits(or a few more) correctly as that is what the sampler would choose anyway. Do they alter existing model for better behavior across all options? Or they distilled one to have the proper behavior? We can only guess without the actual implementation.

You don't even bother text after the [a] at first place in this case

Your question is something like

anwser only a,b,c,d for following question a. b. c. d....

the model output possibility of next character a: 0.8 b: 0.7 c: 0.3 f: 0.2 d: 0.1

If the list contains option you did not provide. The model is confused anyway, it don't matter if you use grammer to filter out the bad option or not, the answer is screwed already.

If you really know what grammers did, grammer is a filter to mask out option llm provided but you don't like.

It does not change potential distribution in any means. It DROPS part of answer model returned directly.

The text generation model go wild because model relies on previous section it answered to continue later section. And because now it contain item model have no idea, it is completely screwed.

In the case you only require model to answer one of a,b,c,d and don't care about later segment at all. It don't really matter.

Fixed guard today is not very fixed. For ex, the safeguard qwen released is a full 4b llm model. It has no different to normal llm model arch except tuned for this specific purpose,

i mean webKit never handle viewport well when compare to firefox or chrome. it's willing to materialize a 10000*10000 texture when firefox and chrome will think that is too dumb and only load the visible part. It's not a good target if you want to compare windows and mac software quality.

I doubt the purpose is even age verification. They already can know I have a visa card which is credit card that can be only applied by an adult by looking at the BIN. Why they need my id card if the purpose is actually age verification?

Plus the routeros supports exporting all settings directly as text file. so you can really export the whole system, send it to llm and ask it to edit. install the new rule.

in worst case you just install the old rule back if it fuck up, no really damage can happen.

Every single asr model I tested so far did not support timestamps properly though. Some use external aligner to create timestamp, but the accuracy is still much inferior than whipser in case the audio is noisy.

Chrome is the only browser that preserve unused bit in value NaN through non JITed mode as far as I remember. And that bit become 0 when code get JITed.

If calling somebody with phone is still 'dialing' someone even there is nothing round on smart phone. Then why not?