updated readme

README.md

@@ -27,4 +27,28 @@ dataset_info:
     num_examples: 27382
   download_size: 2322876358
   dataset_size: 2892669154
+task_categories:
+- text-generation
+- question-answering
+language:
+- en
+tags:
+- biology
+- pytorch
+- causal-lm
+size_categories:
+- 100K<n<1M
 ---
+
+
+# Overview
+
+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". 
+This dataset was constructed from the immune tissue dataset in [Domínguez et al.](https://www.science.org/doi/10.1126/science.abl5197), 
+and it was used to train the [Pythia-160m model](https://huggingface.co/EleutherAI/pythia-160m) capable of generating complete cells described in our paper. 
+Details about the Cell2Sentence transformation and preprocessing pipeline can be found in our paper and GitHub repo linked below.
+
+GitHub: <https://github.com/vandijklab/cell2sentence-ft>  
+Paper: <https://www.biorxiv.org/content/10.1101/2023.09.11.557287v3>  
+Model Card: <https://huggingface.co/vandijklab/pythia-160m-c2s>