Instructions to use Luuu01/RESNETDONE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Luuu01/RESNETDONE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Luuu01/RESNETDONE") 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("Luuu01/RESNETDONE") model = AutoModelForImageClassification.from_pretrained("Luuu01/RESNETDONE") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d577f2b6fe1c3939a2ab4253e4fa864034bbbc1c59b9a0ea555d988c4e98ad0
- Size of remote file:
- 94.3 MB
- SHA256:
- 618c56f023b276d28ea11c268968356e8851026e3e6e5715c2971b781113c339
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.