license: apache-2.0
##Overview
This model uses Cell2Sentence fine-tuning on the Pythia-160m model developed by EleutherAI.
Cell2Sentence Links: GitHub: https://github.com/vandijklab/cell2sentence-ft Paper: https://www.biorxiv.org/content/10.1101/2023.09.11.557287v3
Pythia Links GitHub: https://github.com/EleutherAI/pythia Paper: https://arxiv.org/abs/2304.01373 Hugging Face: https://huggingface.co/EleutherAI/pythia-160m
##Model Details
Cell2Sentence is a novel method for adapting large language models to single-cell transcriptomics. We transform single-cell RNA sequencing data into sequences of gene names ordered by expression level, termed "cell sentences". For more details, we refer to the paper linked above. This model is trained on the immune tissue dataset from Domínguez et al. on the following tasks:
- conditional cell generation
- unconditional cell generation
- cell type prediction