cross-posted from: https://lemmy.sdf.org/post/29607342
Here is the data at Hugging Face.
A team of international researchers from leading academic institutions and tech companies upended the AI reasoning landscape on Wednesday with a new model that matched—and occasionally surpassed—one of China’s most sophisticated AI systems: DeepSeek.
OpenThinker-32B, developed by the Open Thoughts consortium, achieved a 90.6% accuracy score on the MATH500 benchmark, edging past DeepSeek’s 89.4%.
The model also outperformed DeepSeek on general problem-solving tasks, scoring 61.6 on the GPQA-Diamond benchmark compared to DeepSeek’s 57.6. On the LCBv2 benchmark, it hit a solid 68.9, showing strong performance across diverse testing scenarios.
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Hey, I came late to the party. I am CS but I am far from AI. Can you point me to a resource where I can learn how to use all of “those things” that you mention?
Had the same problem and someone guided me to the hugging face documents/tutorials.
They are quite nice to get a local model up and running, play around with it, how to fine tune it and connect it with agents
Haven’t tried much, but the articles were exactly what I was looking for
Hope it helps you as well
Thank you!
As @naeap@sopuli.xyz said, it’s on their Hugging Face site (here the link again: https://huggingface.co/open-thoughts/OpenThinker-32B), just below the first table are all the links.