![]() I’m not seeing any errors and ot_top_losses(5, nrows=1) is showing 5 images correctly. I’ve got the latest NPM and Node installed as of two days ago. I can still do the course materials so it’s not a crisis but I would like to be able to clean my data if possible for the model. The code works as expected on the Kaggle workspace but I have a 4090 on my local machine and training is 5X faster locally than in the cloud so would prefer to be able to use my own machine for it. I’ve tried this both under Windows as well as WSL (I much prefer WSL though since wow it’s so much faster). ![]() I get the same results regardless of using jupyter-lab or jupyter notebook. I’ve tried using the fastai fast setup with mamba (mambo?), as well as using my own install of things using a virtualenv and pip installing things. I’ve tried this in Brave, Chrome, and Edge. If I scroll to the right on the bar other images will flicker in and out but I can never select them for cleaning. ![]() I get a new cell with a single image and a large scroll bar. I’m running into an issue where I’m using the information in chapter 2 of the book to create an image recognition model and when I get to the point where I’m running: cleaner = ImageClassifierCleaner(learn) ![]()
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