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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download setup.py from ctheodoris/Geneformer: direct link, hf CLI and curl.
- Browser
- Download file 637 Bytes
-
https://huggingface.co/ctheodoris/Geneformer/resolve/8ce598f054a680517c647207f52d09963f7abd89/setup.py
- Command line
-
hf download hf://ctheodoris/Geneformer@8ce598f054a680517c647207f52d09963f7abd89/setup.py
-
curl -L -o setup.py https://huggingface.co/ctheodoris/Geneformer/resolve/8ce598f054a680517c647207f52d09963f7abd89/setup.py
637 Bytes
| from setuptools import setup | |
| setup( | |
| name="geneformer", | |
| version="0.0.1", | |
| author="Christina Theodoris", | |
| author_email="christina.theodoris@gladstone.ucsf.edu", | |
| description="Geneformer is a transformer model pretrained \ | |
| on a large-scale corpus of ~30 million single \ | |
| cell transcriptomes to enable context-aware \ | |
| predictions in settings with limited data in \ | |
| network biology.", | |
| packages=["geneformer"], | |
| include_package_data=True, | |
| install_requires=[ | |
| "datasets", | |
| "loompy", | |
| "numpy", | |
| "transformers", | |
| ], | |
| ) | |