Instructions to use ahyar002/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahyar002/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahyar002/image_classification") 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("ahyar002/image_classification") model = AutoModelForImageClassification.from_pretrained("ahyar002/image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20a0e4511aa0f1ecf423f0add757c76d6e835d06e82cee08da53b2f44360923e
- Size of remote file:
- 4.09 kB
- SHA256:
- e20874b6ee9e61cf64135b601afb883c4b8278cfa753659a1d4cd8e1624e09bd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.