Instructions to use the-clueless-classifier/SCUTFVD-resnet50-fold02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use the-clueless-classifier/SCUTFVD-resnet50-fold02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="the-clueless-classifier/SCUTFVD-resnet50-fold02") 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("the-clueless-classifier/SCUTFVD-resnet50-fold02") model = AutoModelForImageClassification.from_pretrained("the-clueless-classifier/SCUTFVD-resnet50-fold02", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 475a1baa7de1a86ace419ceb57f2800ffdf93d62c033174c5366f46a37aff68f
- Size of remote file:
- 5.2 kB
- SHA256:
- b2cdf7c30310fc06ee9a2a159f23ddd36878c46ff41cf0e645d557800244b7b5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.