mims-harvard/CASCADE-Alzheimer

scRep is a PyTorch model for extracting cell embeddings from single-cell RNA-seq AnnData (.h5ad) inputs. This repository is a standalone Hugging Face release bundle: it includes checkpoint weights, the exact paired gene vocabulary, the inference implementation, and runnable examples.

Nicheformer is a transformer-based model designed for understanding and predicting cellular niches and their interactions. The model uses masked language modeling to learn representations of cellular contexts and their relationships.

Tahoe-x1 is a family of perturbation-trained single-cell foundation models with up to 3 billion parameters, developed by Tahoe Therapeutics. Pretrained on 266 million single-cell transcriptomic profiles including the Tahoe-100M perturbation compendium, Tahoe-x1 achieves state-of-the-art performance…

PhenoSeq is a Gaussian diffusion model that generates scGPT RNA-seq embeddings conditioned on ViT-L microscopy imaging features. Given fluorescence microscopy images of a cell or well, it predicts a 512-dimensional scGPT embedding representing the transcriptomic state of individual cells — enabling…

# nano-scGPT The simplest, fastest repository for scGPT inference, (soon) finetuning and trianing, with minimal dependencies. It reimplements the original scGPT from scratch. nanoscgpt/model.py is pure PyTorch in ~270 lines of code, and nanoscgpt/scGPT_tokenizer.py turns raw scRNA data into model…

# FremyCompany/BioLORD-2023-M This model was trained using BioLORD, a new pre-training strategy for producing meaningful representations for clinical sentences and biomedical concepts.