Image Classification
Transformers
PyTorch
TensorBoard
resnet
Generated from Trainer
Eval Results (legacy)
Instructions to use jayanta/resnet50-finetuned-memes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayanta/resnet50-finetuned-memes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jayanta/resnet50-finetuned-memes") 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("jayanta/resnet50-finetuned-memes") model = AutoModelForImageClassification.from_pretrained("jayanta/resnet50-finetuned-memes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c1cfde6e2a9e0d457144a2deb830b524c84ff410b016eb42031e1a860ad33ce
- Size of remote file:
- 94.4 MB
- SHA256:
- af77bf2e870d0dd43e512fd1c4682d76d63c108dda4ebf935e14f9d3c7d7327f
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