Instructions to use Falcom/animal-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falcom/animal-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Falcom/animal-classifier") 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("Falcom/animal-classifier") model = AutoModelForImageClassification.from_pretrained("Falcom/animal-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebf34d64b160e08c82f1a1e73f86f61944548a2c72ba22a32c4bf04aba5a35ec
- Size of remote file:
- 343 MB
- SHA256:
- cb7fdc060c0c89386ddbec8afc303e9b2bf0dfce1887fc8bf4616dfaebb97715
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