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README.md

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+---
+license: mit
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- materials
+- xrd
+- diffraction
+- crystal-structure
+- inverse-design
+- jarvis
+pretty_name: DiffractGPT-DFT (XRD to crystal structure)
+---
+
+# DiffractGPT-DFT
+
+Alpaca-format dataset for the **inverse powder-XRD problem**: given a chemical
+formula and the main 2-theta peaks of a Cu-K-alpha pattern, generate the crystal
+structure. **73,374 train / 8,152 validation** structures from JARVIS-DFT
+`dft_3d`. Same text format as [`knc6/diffractgpt_jarvis_dft`](https://huggingface.co/datasets/knc6/diffractgpt_jarvis_dft),
+rebuilt on a fixed split used to benchmark multiple base LLMs for XRD-to-structure.
+
+## Record format (4 fields)
+| field | content |
+|---|---|
+| `instruction` | `Below is a description of a material.` |
+| `input` | formula + top-20 XRD peaks `<2theta>deg(<rel intensity>)` + a request for the structure |
+| `id` | JARVIS identifier |
+| `output` | `a b c` (A) / `alpha beta gamma` (deg) / one `Element x y z` line per atom |
+
+Models: https://huggingface.co/knc6/diffractgpt_dft_models ; code:
+https://github.com/atomgptlab/diffractgpt ; underlying data: JARVIS-DFT
+(https://doi.org/10.1038/s41524-020-00440-1).