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
-
Fix bug with metadata when processing multiple .loom files
36a4b06
-
Update token_dictionary.pkl
1987df4 -
Delete geneformer/token_dictionary.pkl
870b99b
-
Update README.md
add Genecorpus-30M link5e1ff99
-
Add data collator for gene classification and example for gene classification
Christina Theodorisedacd12
-
Add data collator for cell classification and example for cell classification
Christina Theodoris088ea6e
-
update model card with installation instructions
f0de016
-
Add alternative methods comparison examples
Christina Theodoris277b470
-
Update README.md
Update model cardc33c308
-
Add Geneformer trainer and pretraining example
Christina Theodorisbcc03e8 -
Add Geneformer tokenizer and updated model card
Christina Theodoris5426788 -
Add setup.py
b73028f -
Add MANIFEST.in
1163e5e
-
update README.md
Christina Theodoris1ff02e6
-
create Geneformer model card
Christina Theodoris453894a
-
upload training args for Geneformer 6L-30M
Christina Theodoris4cfe5a6 -
upload Geneformer 6L-30M config
Christina Theodorisc45a71b -
upload Geneformer 6L-30M
Christina Theodoris3c8dcdc -
initial commit
Christina Theodorisc6d4a49