Nice job! This is a fantastic resource for anyone interested in using contrastive methods for inducing AI/ML models to learn to embed data in a space such that

Nice job! This is a fantastic resource for anyone interested in using contrastive methods for inducing AI/ML models to learn to embed data in a space such that samples considered similar stay close to each other (e.g., as measured by cosine or Euclidean distance) while dissimilar ones stay far apart. Self-supervised contrastive methods, in particular, can be remarkably useful when none of the samples in your data are labeled and you want your model to discover structure.