Instructions to use pyronear/resnet18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pyronear/resnet18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pyronear/resnet18") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pyronear/resnet18", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0a018db169bd0db999e9a032351210a07d90ef4412d6a2f1883df81230aeb7f
- Size of remote file:
- 44.8 MB
- SHA256:
- 40b9e7d91df68f1f858454d28a66914d45124886cd83b2e774459ad8010a8885
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.