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It was trained on ~36M tokens from [ua-codeforces-cots-open-r1](https://huggingface.co/datasets/anon-researcher-ua/ua-codeforces-cots-open-r1) ([ua-codeforces-cots-open-r1-for-training](https://huggingface.co/datasets/anon-researcher-ua/ua-codeforces-cots-open-r1-for-training) in fact), which extends [open-r1/codeforces-cots](https://huggingface.co/datasets/open-r1/codeforces-cots) with translated Ukrainian problem statements and low/medium/high reasoning traces.
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The model supports low, medium, and high reasoning effort as well as language control for reasoning via system prompts.
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This model is able to reason in other languages as well with proper sampling params (check examples below).
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# Training Details
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It was trained on ~36M tokens from [ua-codeforces-cots-open-r1](https://huggingface.co/datasets/anon-researcher-ua/ua-codeforces-cots-open-r1) ([ua-codeforces-cots-open-r1-for-training](https://huggingface.co/datasets/anon-researcher-ua/ua-codeforces-cots-open-r1-for-training) in fact), which extends [open-r1/codeforces-cots](https://huggingface.co/datasets/open-r1/codeforces-cots) with translated Ukrainian problem statements and low/medium/high reasoning traces.
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The model supports low, medium, and high reasoning effort as well as language control for reasoning via system prompts.
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This model is able to reason in other languages as well with proper sampling params ([check examples below](https://huggingface.co/anon-researcher-ua/codegpt-oss-20b#other-languages)).
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# Training Details
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