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Hello,
Thank you very much for your work! I'm excited to run your model on our spatial data and finetune it for niche regression. So, I first used the get_embeddings notebook to embed one of my datasets. And now, I'm using the fine tuning notebook to train a model that can predict niche labels.
But I've been facing three issues:
- I've read the paper, but I'm unsure if cell-typing is a feature in nicheformer. Because the setting for supervised_task in config seems to take different inputs like
'classification', 'regression', 'niche_regression', 'density_regression', 'niche_classification', 'niche_binary_classification', 'niche_multiclass_classification'
. Are these all only associated with niche/spatial related predictions? PS: I got these looking upsupervised_task
in your codebase. Please correct me if my assumptions are wrong and help clarify what each option does. - I'm not sure what the
baseline=False
setting is supposed to do inNicheformerFineTune()
. So I commented it out because I was getting an error saying it was an invalid argument. - And finally, when I run the notebook to finetune a model for niche_regression, I cannot get past the sanity check and end up with
keyError: 'modality'
at the end of the error stack.
For reproducibility, I have attached some sample data and the html rendering of my notebook. Any advice is highly appreciated!
Thank you,
Mar
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