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/extract_and_plot_cell_embeddings.ipynb from tdc/Geneformer: direct link, hf CLI and curl.
- Browser
- Download file 1.13 MB
-
https://huggingface.co/tdc/Geneformer/resolve/aa7c98986b9972503f84b077dcbf58300aab5b0f/examples/extract_and_plot_cell_embeddings.ipynb
- Command line
-
hf download hf://tdc/Geneformer@aa7c98986b9972503f84b077dcbf58300aab5b0f/examples/extract_and_plot_cell_embeddings.ipynb
-
curl -L -o extract_and_plot_cell_embeddings.ipynb https://huggingface.co/tdc/Geneformer/resolve/aa7c98986b9972503f84b077dcbf58300aab5b0f/examples/extract_and_plot_cell_embeddings.ipynb
1.13 MB