# Distillation Model

Quasar-3.0-7B is the distilled version of the upcoming 400B Quasar 3.0 model, showcasing the early strength and potential of the Quasar architecture.

A text ranking cross-encoder based on the ELECTRA architecture, designed for retrieval result reranking tasks

Distill-Any-Depth is a model for depth estimation, based on the transformers architecture, suitable for estimating depth information from images.

This is a machine translation model supporting bidirectional translation between 22 Indian languages and English, optimized using distillation techniques with a parameter size of 200M.

This model is a text summarization model fine-tuned on the BBC News Summary dataset based on sshleifer/distilbart-cnn-12-6, developed by the Deep Natural Language Processing Course Lab at Politecnico di Torino.

TinySapBERT is a compact biomedical entity representation model trained on the SapBERT framework, specifically designed for biomedical named entity recognition tasks.

This is a Korean-English bilingual sentence embedding model based on sentence-transformers, which maps sentences to a 768-dimensional vector space, suitable for semantic search and clustering tasks.