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
Commit History
Upload in_silico_perturber.py (#432) cb89107 verified
Update geneformer/emb_extractor.py (#453) ebc1e09 verified
Update geneformer/tokenizer.py (#450) 664f71e verified
update isp default mode to cls 0c99403 verified
Adding tags to the model (#448) 3a68669 verified
update transformers version to match pretrainer using accelerate 3d62bb9 verified
update pretrainer to not use distributed sampler (Trainer uses accelerate) 8140c51 verified
update function for N_Detections for mixture_model without anchor_token df297bc
Christina Theodoris commited on
add check to ensure emb_label is None for getting state embs dict 39b4444
Christina Theodoris commited on