Datasets:

knc6
/

diffractgpt_jarvis_dft

pretty_name: diffractgpt_jarvis_dft (XRD Spectra → Structure)
license: mit
tags:
  - materials-science
  - text-to-structure
  - text2text-generation
  - instruction-tuning
task_categories:
  - text2text-generation
dataset_info:
  features:
    - name: id
      dtype: string
    - name: instruction
      dtype: string
    - name: input
      dtype: string
    - name: output
      dtype: string
  splits:
    - name: train
      num_bytes: null
      num_examples: null
    - name: test
      num_bytes: null
      num_examples: null
language:
  - en

diffractgpt_jarvis_dft (XRD Spectra → Structure)

Goal. Map a textual description of a material (composition + XRD peaks, etc.) to a compact crystal structure description (lattice lengths, angles, fractional coordinates, atom types).

Data Fields

id (str): source identifier (e.g., POSCAR/JVASP id).
instruction (str): the generic instruction.
input (str): material description (composition, XRD, etc.).
output (str): target structure text (lattice lengths/angles + fractional coords).

Splits

train.json
test.json

Quickstart

from datasets import load_dataset

ds = load_dataset("knc6/diffractgpt_jarvis_dft", data_files={
    "train": "train.json",
    "test": "test.json"
})
print(ds)
print(ds["train"][0])