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")# pip install -U transformers accelerate # 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
Commit History
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Config head node runtime via IP (#234)
- Config head node runtime via IP (748f48ac03faa90488220eb2f9b5a76e128a6c06) - Update minor formatting (c48e37c67945c09e6593d45c40c4cbe0df7cc757) Co-authored-by: Madhavan Venkatesh <madhavanvenkatesh@users.noreply.huggingface.co>b8fda63
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Change list of individual IDs to set to ensure unique before subsetting into train/valid/test sets
Christina Theodoris45b9d69
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Add example for hyperparameter optimization for disease classifier
Christina Theodoris79a0c41