Instructions to use Kaz369/resnet18-random-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Kaz369/resnet18-random-classifier with timm:
import timm model = timm.create_model("hf_hub:Kaz369/resnet18-random-classifier", pretrained=True) - Transformers
How to use Kaz369/resnet18-random-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Kaz369/resnet18-random-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Kaz369/resnet18-random-classifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add model
Browse files- model.safetensors +1 -1
- pytorch_model.bin +1 -1
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