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William Suffill

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liked a dataset about 2 months ago
jupyter-agent/jupyter-agent-dataset
reacted to hannayukhymenko's post with 👍 about 2 months ago
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
reacted to louisbrulenaudet's post with 👍 2 months ago
Supercharge Apple’s Shortcuts using Cloudflare Workers and Gemini within minutes (and for free, up to 1,500 requests per day) ☁️✨ Hello everyone, last week, while experimenting for fun, I created an API that allows you to easily access AI models (in this case, Google's) from the Shortcut app in order to analyze data from my apps and make the most of it thanks to the generative capabilities of advanced models. It costs me nothing, and I think it might be good to share it so that others can build on it. In README.md, you will find everything you need to get started and put your own microservice into production, which you can call from the app’s HTTP request features. You will simply be asked to have a free Cloudflare account and an API key obtained from Google's AI Studio. Feel free to take a look and get back to me if you encounter any problems during deployment. Here is the GitHub repo where you can find all the source code and run it on your own: https://github.com/louisbrulenaudet/genai-api
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