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Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

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01gui-wm /agentnet-success-v1 agentnet-success-v1 GUI state transitions (s, a, s') walked on an Ubuntu desktop by Qwen3.8-27B, from tasks taken from AgentNet and run inside OSWorld's Docker environment. Walks the judge ruled had finished the task. Use these to score an agent: the trajectory is a worked example, and action_target gives the element each step was aiming at, so an answer can be marked right by control rather than by pixel. This repository is the one-condition pool. Tasks are drawn from the 623… See the full description on the dataset page: https://huggingface.co/datasets/gui-wm/agentnet-success-v1.textimage-to-textn<1K1 likes567 downloads14d agoHugging Face02GUIAgentt /koen-web-agent-sft-mixesgated Korean-English Web Agent SFT Mixes 브라우저 GUI 에이전트 SFT 용 한국어·영어 혼합 데이터. 언어 비율만 다르고 나머지는 동일하게 통제된 4개 구성이라, 비율이 성능에 미치는 영향을 직접 비교할 수 있다. 구성 config ko : en 스텝 궤적 ko_only_20k 10 : 0 20,001 3,042 mix_ko_en_5050 5 : 5 20,008 2,663 mix_ko_en_2080 2 : 8 20,003 2,436 en_only_20k 0 : 10 20,009 2,274 비율은 궤적 수가 아니라 스텝 수 기준이다. 스텝 하나가 학습 샘플 하나인데 한국어 궤적은 평균 6.6스텝, 영어는 8.7스텝이라, 궤적 수로 5:5 를 맞추면 실제 gradient 기여가 5:5 가 되지 않는다. 궤적은 절대 쪼개지 않는다. 네 구성의 표본은 서로 중첩된다.… See the full description on the dataset page: https://huggingface.co/datasets/GUIAgentt/koen-web-agent-sft-mixes.tabular10K<n<100K0 likes10 downloads1mo agoHugging Face

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