Instructions to use jsli96/ResNet-18-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jsli96/ResNet-18-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jsli96/ResNet-18-1") 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("jsli96/ResNet-18-1") model = AutoModelForImageClassification.from_pretrained("jsli96/ResNet-18-1") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
7367dfa | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:0aa8d5652935be63cda6defc0428de0798b7c6501ee1307eb5a6c531f8df92b3
size 45197877
|