Instructions to use tdc/Geneformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tdc/Geneformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tdc/Geneformer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tdc/Geneformer") model = AutoModelForMaskedLM.from_pretrained("tdc/Geneformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download examples/gene_classification.ipynb from tdc/Geneformer: direct link, hf CLI and curl.
- Browser
- Download file 180 kB
-
https://huggingface.co/tdc/Geneformer/resolve/1b531a57070efd45ef2d73f0e399f5ab40e5a3ea/examples/gene_classification.ipynb
- Command line
-
hf download hf://tdc/Geneformer@1b531a57070efd45ef2d73f0e399f5ab40e5a3ea/examples/gene_classification.ipynb
-
curl -L -o gene_classification.ipynb https://huggingface.co/tdc/Geneformer/resolve/1b531a57070efd45ef2d73f0e399f5ab40e5a3ea/examples/gene_classification.ipynb
180 kB