[P] Tranformer-based Denoising AutoEncoder for Sentence Transformers Unsupervised pre-training

# A new PyPI package for training sentence embedding models in just 2 lines.

The acquisition of sentence embeddings often necessitates a substantial volume of labeled data. However, in many cases and fields, labeled data is rarely accessible, and the procurement of such data is costly. In this project, we employ an unsupervised process grounded in pre-trained Transformers-based Sequential Denoising Auto-Encoder (TSDAE), introduced by the Ubiquitous Knowledge Processing Lab of Darmstadt, which can realize a performance level reaching 93.1% of …

acquisition autoencoder cases data denoising embedding embedding models embeddings fields machinelearning package pre-training procurement project pypi training transformers unsupervised