Submitted by michaelthwan_ai t3_121domd in MachineLearning
addandsubtract t1_jdlvmm6 wrote
Where does GPT-J and dolly fall into this?
wywywywy t1_jdlz40b wrote
GPT-J & GPT-Neo are predecessors of GPT-NeoX 20b
michaelthwan_ai OP t1_jdlzwyi wrote
Sure I think it is clear enough to show parents of recent model (instead of their grand grand grand parents..
If people want, I may consider to make a full one (including older one)
wywywywy t1_jdm16va wrote
In my opinion, it'd be better to include only the currently relevant ones rather than everything under the sun.
Too much noise makes the chart less useful.
michaelthwan_ai OP t1_jdm3sgb wrote
Agreed
Puzzleheaded_Acadia1 t1_jdlx6ea wrote
Is gpt-j 6b really better than alpaca 7b and Wich run faster
DigThatData t1_jdmvquq wrote
the fact that it's comparable at all is pretty wild and exciting
StellaAthena t1_jdotklz wrote
It’s somewhat worse and a little faster.
[deleted] t1_jdlzp51 wrote
[deleted]
michaelthwan_ai OP t1_jdlztvv wrote
It is a good model but it's about one year ago, and not related to recent released LLM. Therefore I didn't add (otherwise a tons of good models).
For dolly, it is just ytd. I didn't have full info of it yet
addandsubtract t1_jdm1d9h wrote
Ok, no worries. I'm just glad there's a map to guide the madness going on, atm. Adding legacy models would be good for people who come across them now, to know that they are legacy.
DigThatData t1_jdmvjyb wrote
dolly is important precisely because the foundation model is old. they were able to get chatgpt level performance out of it and they only trained it for three hours. just because the base model is old doesn't mean this isn't recent research. it demonstrates:
- the efficacy of instruct finetuning
- that instruct finetuning doesn't require the worlds biggest most modern model or even all that much data
dolly isn't research from a year ago, it was only just described for the first time a few days ago.
EDIT: ok I just noticed you have an ERNIE model up there so this "no old foundation models" thing is just inconsistent.
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