Yes! I'm looking forward to R2
I tested and ranked every model drop for my leaderboard https://huggingface.co/spaces/onekq-ai/WebApp1K-models-leaderboard but this time I gave up.
Whatever questions this model aims to solve, they are out of my league.
You can infer on CPU, but it will be very very slow 😕
Welcome to my world 😎
Question for the Llama team: what will be your play? 😅
Not implying. I like to know what the base is. If QwQ and DeepSeek distill use the same base, then it becomes more puzzling why the performance differ so much.
Ah I see. Thanks!
Still the blogpost didn't mention what the base model is (if any).
Cool! I will check it out.
What I meant by switching is this. Sometimes I'm not satisfied with ChatGPT answer, and realized it needs to think harder. So I switched to o1 and asked again, and most of the times the answer gets better. Then I asked a simple follow-up question which o1 overanalyzed. Then I had to switch back to gpt-4o. I don't actually have the foresight which model fits my question the best. I only know it after I read the answer which is too late.
Now imagine a conversation with a human expert. A human can do such switching remarkably well, hence a cool conversation. This can be actually a metric to read the mileage of an applicant.
