Instructions to use ctheodoris/Geneformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctheodoris/Geneformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ctheodoris/Geneformer")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ctheodoris/Geneformer") model = AutoModelForMaskedLM.from_pretrained("ctheodoris/Geneformer") - Inference
- Notebooks
- Google Colab
- Kaggle
Cardiomyocyte Dataset Pre-Processing
Hello,
I am planning to replicate your disease modeling experiments using a different foundational model that requires raw counts as input. Could you please let me know if you applied any preprocessing to the cardiomyocyte dataset, aside from rank value encoding?
Thank you for your question! This repository is meant for questions about the code. Please take the standard approach of emailing the corresponding author to discuss questions about the paper. Please see the paper methods for the methods used for preprocessing the cardiomyocyte dataset, which was the method used by the original authors of this dataset.
Thank you for your prompt response and for clarifying the focus of the repository. In the future, I will make sure to contact the corresponding authors directly to discuss any questions I have about the paper.