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![Michael Platzer](https://ph-avatars.imgix.net/483116/original.jpeg?auto=compress&codec=mozjpeg&cs=strip&auto=format&w=48&h=48&fit=crop&frame=1)
DataLLM enables the generation of realistic, diverse, and context-aware tabular data via LLM prompts. It supports conditional generation, data types, regex, and more, facilitating data mocking, enrichment, and cleansing directly from your Python prompt.
![DataLLM](https://ph-files.imgix.net/8e4f9d29-019a-487d-9069-fd14d05fa696.jpeg?auto=compress&codec=mozjpeg&cs=strip&auto=format&w=48&h=48&fit=crop&frame=1)
DataLLM
prompt LLMs for Tabular Data 🔮