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13.1
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Hanna Yukhymenko
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Multilingual efficiency/safety @ ETHZ
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Releasing the Jupyter Agent Dataset! 🚀 Built from 7 TB of real Kaggle datasets + 20k notebooks, creating real code exec traces using Qwen3-Coder and E2B. Training on this data dramatically improves the ability to execute code and analyze data. We (@baptistecolle @hannayukhymenko @lvwerra) have created a novel synthetic data generation pipeline with efficient scaffolding, which gives a big performance boost after training your coding agent🔥With the help of real Kaggle notebooks and datasets we generate synthetic notebooks which aim to analyze datasets and answer factual questions about them more efficiently. We simulate a real code execution environment by prompting LLMs or with the help of E2B sandboxes. We have built a dataset of 50k+ high-quality LLM-generated notebooks which can help your agent become better at performing data analysis and question answering. Link: https://huggingface.co/datasets/data-agents/jupyter-agent-dataset
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Mamay V0.1 Chat
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MamayLM-v0.1 test chat interface
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Synthpai Inference
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