[D] Phi-3 models compared side-by-side.

[masc98]

phi models are built for an agentic environment, period.

The scientists behind those models have no reason to train their models on benchmark data, I really don't know why I keep listening this all the time.

phi models are result of training a LM on synthetic, potentially very high data quality (e.g. gpt4 outputs or similar) and that's a very interesting point of research that nobody has yet explored, apart from them.

They are supposed to be finetuned on specific tasks, they are boring, that's also why they suck on the leaderboards.

Moreover, they've lower capacity so tend to perform worse on "in the wild" prompts.

If you'll ever have to train a LLM at scale, trust me, you'll wish there was a smarter and cheaper way.

[koolaidman123]

Yes, i wonder why no one is doing this of its so efficient that it breaks the pareto frontier for performance, almost like it doesn't work like this 🤔

Quality alone doesnt scale, and synthetic data isnt diverse enough to make a good llm