MultiMolecule

MultiMolecule is a one-stop ecosystem for molecular machine learning. It connects datasets, model implementations, reusable dataset and neural-network modules, the DanLing-based runner for training and evaluation, and task-oriented inference pipelines for RNA, DNA, and protein workflows.

Get Started

Install the latest stable release from PyPI:

pip install multimolecule

Run a registered pipeline through the Hugging Face transformers interface:

import multimolecule  # registers MultiMolecule models and pipelines
from transformers import pipeline

predictor = pipeline("rna-secondary-structure", model="multimolecule/ernierna-ss")
result = predictor("AUCAGCCUUCGUUCUGUAAACGG")

Load models directly when you need lower-level control:

import multimolecule

model = multimolecule.AutoModelForSequencePrediction.from_pretrained("multimolecule/basset")
tokenizer = multimolecule.AutoTokenizer.from_pretrained("multimolecule/basset")

Install the latest source version when you need unreleased changes:

pip install git+https://github.com/DLS5-Omics/MultiMolecule

Explore

Community

• Discourse: release announcements, usage questions, model requests, RFCs, and community discussion.
• GitHub Issues: reproducible bugs, API issues, and implementation-tracked feature requests.
• Hugging Face: released checkpoints, datasets, and demo Spaces.

Citation

@software{chen_2024_12638419,
  author    = {Chen, Zhiyuan and Zhu, Sophia Y.},
  title     = {MultiMolecule},
  doi       = {10.5281/zenodo.12638419},
  publisher = {Zenodo},
  url       = {https://doi.org/10.5281/zenodo.12638419},
  year      = 2024,
  month     = may,
  day       = 4
}

License

We believe openness is the Foundation of Research.

MultiMolecule is licensed under the GNU Affero General Public License.

For additional terms and clarifications, please refer to our License FAQ.

Please join us in building an open research community.

SPDX-License-Identifier: AGPL-3.0-or-later