Instructions to use suhnylla/planes_airlines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suhnylla/planes_airlines with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="suhnylla/planes_airlines") 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("suhnylla/planes_airlines") model = AutoModelForImageClassification.from_pretrained("suhnylla/planes_airlines", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63282145bf3a65a3055639c716b8aac4809e02b62557b49a3a05c95a05ebf1e6
- Size of remote file:
- 343 MB
- SHA256:
- cb01517e12dec1c23c0e9b8cdd0f1c8e7f1663baea93fc96b84a53830ff213a2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.