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
example `cell_type_train_data.dataset`?
Hi,
Great work! I am willing to use Geneformer right now. Do you have any plans on uploading an example "/path/to/cell_type_train_data.dataset" file, or/and providing a tutorial on how to convert standard single cell count data into a valid dataset to feed into Geneformer?
Thanks!
update: Sorry I missed the closed discussions on this. Now I just want to know whether this is on the plan, since I see you are actively updating the repo! : )
same here
Thank you for your interest in Geneformer.
Regarding the example input files: please see the updated discussion in the closed issue https://huggingface.co/ctheodoris/Geneformer/discussions/16.
Regarding how to tokenize datasets with the transcriptome tokenizer, we added an example here: https://huggingface.co/ctheodoris/Geneformer/tree/main/examples
Thank you for your interest in Geneformer.
Regarding the example input files: please see the updated discussion in the closed issue https://huggingface.co/ctheodoris/Geneformer/discussions/16.
Regarding how to tokenize datasets with the transcriptome tokenizer, we added an example here: https://huggingface.co/ctheodoris/Geneformer/tree/main/examples
Thanks!