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- image-classification
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- pytorch
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- huggingpics
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metrics:
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- accuracy
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model-
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- name: pneumonia_test_attempt
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results:
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- task:
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name: Image Classification
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type: image-classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9783163070678711
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---
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# pneumonia_test_attempt
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Autogenerated by HuggingPics🤗🖼️
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Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
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Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
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## Example Images
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#### NORMAL
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
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#### PNEUMONIA
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
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pneumonia-bielefeld-dl-course
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This registry contains the model for making pneumonia predictions and was prepared for Bielefeld University Deep Learning course homework.
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The code used for this implementation mostly comes from here: https://github.com/nateraw/huggingpics it was a ready pipeline for model fine-tuning with huggingface and PyTorch Lightning for another dataset.
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