State provenance of the prompt field (FunctionGemma chat template)
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README.md
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@@ -182,6 +182,15 @@ The rows are programmatic expansions of hand-written English stems — no model
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scraped corpus is involved, and no personal data is present. The paths and filenames in the slot
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pools are generic placeholders (`~/Downloads`, `invoice`, `screenshot`), not real user data.
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**One caveat about downstream use.** This data is MIT, but the *model* trained on it in this
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project is a FunctionGemma derivative and is governed by the
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[Gemma Terms of Use](https://ai.google.dev/gemma/terms) — the dataset licence does not and cannot
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scraped corpus is involved, and no personal data is present. The paths and filenames in the slot
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pools are generic placeholders (`~/Downloads`, `invoice`, `screenshot`), not real user data.
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**Provenance of the `prompt` field.** The utterances, the tool labels and the argument values are
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original work and are MIT. The `prompt` field, however, is those utterances rendered through
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FunctionGemma's chat template — so it carries that model's control tokens and declaration syntax
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(`<start_function_declaration>`, `<escape>`, and so on). No Gemma model generated any text here;
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`data/generate.py` loads the tokenizer only to apply its template. We take the view that a prompt
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format is an interchange schema rather than model output, and licence the data MIT accordingly —
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but the provenance is stated plainly so you can form your own view. The `tool` and `args` fields in
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`meta.jsonl` are format-independent if you would rather re-render the prompts for another model.
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**One caveat about downstream use.** This data is MIT, but the *model* trained on it in this
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project is a FunctionGemma derivative and is governed by the
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[Gemma Terms of Use](https://ai.google.dev/gemma/terms) — the dataset licence does not and cannot
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