OpenFold at the time of the release of our original model parameters and training database. Adds countless improvements over the previous beta release, including, but not limited to: Many bugfixes contribute to stabler, more correct, and more versatile training Options to run OpenFold using our original weights Custom attention kernels and alternative attention implementations that greatly reduce peak memory usage A vastly superior Colab notebook that runs inference many times faster than the original Efficient scripts for computation of alignments, including the option to run MMSeqs2's alignment pipeline Vastly improved logging during training & inference Careful optimizations for significantly improved speeds & memory usage during both inference and training Opportunistic optimizations that dynamically speed up inference on short (< ~1500 residues) chains Certain changes borrowed from updates made to the AlphaFold repo, including bugfixes, GPU relaxation, etc. "AlphaFold-Gap" support allows inference on complexes using OpenFold and AlphaFold weights WIP OpenFold-Multimer implementation on the multimer branch Improved testing for the data pipeline Partial CPU offloading extends the upper limit on inference sequence lengths Docker support Missing features from the original release, including learning rate schedulers, distillation set support, etc. Full Changelog: https://github.com/aqlaboratory/openfold/compare/v0.1.0...v1.0.0

For now, cite OpenFold with its DOI.