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Thom Lake

@thomlake.bsky.social

Principal Scientist at Indeed. PhD Student at UT Austin. AI, Deep Learning, PGMs, and NLP.

6 Posts708 Follower410 Folgt
Kyle Lo @ ICML2026 🇰🇷@kylelo.bsky.social · 2y ago

Excited to share OLMo 2! 🐟 7B and 13B weights, trained up to 4-5T tokens, fully open data, code, etc 🐠 better architecture and recipe for training stability 🐡 staged training, with new data mix Dolmino🍕 added during annealing 🦈 state-of-the-art OLMo 2 Instruct models #nlp #mlsky links below👇

A scatter plot comparing language models by performance (y-axis, measured in average performance on 10 benchmarks) versus training computational cost (x-axis, in approximate FLOPs). The plot shows OLMo 2 models (marked with stars) achieving Pareto-optimal efficiency among open models, with OLMo-2-13B and OLMo-2-7B sitting at the performance frontier relative to other open models like DCLM, Llama 3.1, StableLM 2, and Qwen 2.5. The x-axis ranges from 4x10^22 to 2x10^24 FLOPs, while the y-axis ranges from 35 to 70 benchmark points.