Instructions to use atomgptlab/diffractgpt_mistral_chemical_formula with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use atomgptlab/diffractgpt_mistral_chemical_formula with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-bnb-4bit") model = PeftModel.from_pretrained(base_model, "atomgptlab/diffractgpt_mistral_chemical_formula") - Notebooks
- Google Colab
- Kaggle
| base_model: unsloth/mistral-7b-bnb-4bit | |
| library_name: peft | |
| license: mit | |
| language: | |
| - en | |
| tags: | |
| - chemistry | |
| - text-generation-inference | |
| - atomgpt | |
| - diffraction | |
| pipeline_tag: text-generation | |
| # DiffractGPT: Atomic Structure Determination from X-ray Diffraction Patterns Using a Generative Pretrained Transformer | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| <!-- Provide a longer summary of what this model is. --> | |
| GitHub: [https://github.com/atomgptlab/atomgpt](https://github.com/atomgptlab/atomgpt) | |
| Web app: [https://atomgpt.org/xrd](https://atomgpt.org/xrd) | |
| [Example colab notebook](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/DiffractGPT_example.ipynb) | |
| Dataset: [https://huggingface.co/datasets/knc6/diffractgpt_jarvis_dft](https://huggingface.co/datasets/knc6/diffractgpt_jarvis_dft) | |
| Reference: [Choudhary, K. (2025). DiffractGPT: Atomic Structure Determination from X-ray Diffraction Patterns Using a Generative Pretrained Transformer. The Journal of Physical Chemistry Letters, 16, 2110–2119.](https://pubs.acs.org/doi/10.1021/acs.jpclett.4c03137) | |
| - | |
| ### Framework versions | |
| - PEFT 0.11.1 | |