Instructions to use eren23/pneumonia_test_attempt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eren23/pneumonia_test_attempt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="eren23/pneumonia_test_attempt") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("eren23/pneumonia_test_attempt") model = AutoModelForImageClassification.from_pretrained("eren23/pneumonia_test_attempt") - Notebooks
- Google Colab
- Kaggle
pneumonia-bielefeld-dl-course
This registry contains the model for making pneumonia predictions and was prepared for Bielefeld University Deep Learning course homework.
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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Evaluation results
- Accuracyself-reported0.978