Instructions to use Starmaster7/bird_genus_image_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Starmaster7/bird_genus_image_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Starmaster7/bird_genus_image_classification_model") 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("Starmaster7/bird_genus_image_classification_model") model = AutoModelForImageClassification.from_pretrained("Starmaster7/bird_genus_image_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0bfeff4b8f17fa77c92f60a75b1b17a6195fa1beec5cde2e3b6f9b3d5ff8c32
- Size of remote file:
- 5.14 kB
- SHA256:
- f2d2322d76c8a335b586a92d12a7ee32217f91e4bf4601bc94fd1878295ba599
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