SimCSE We propose a simple contrastive learning framework that works with both unlabeled and labeled data. Unsupervised SimCSE simply takes an input sentence and predicts itself in a contrastive learning framework, with only standard dropout used as noise. Our supervised SimCSE incorporates annotated pairs from NLI datasets into contrastive learning by using entailment pairs as positives and contradiction pairs as hard negatives. The following figure is an illustration of our models. Use our models out of the box Our pre-trained […]

OpenPNM OpenPNM is a comprehensive framework for performing pore network simulations of porous materials. For more details about the package can be found in the on-line documentation To be notified of new releases click the Watch button on the Github repo page. To show your support for this project click the Star button, as we use this as a proxy for the size of our userbase when applying for funding. Installation and Requirements Preferred method The preferred way of installing […]