Instructions to use Manasee27/cv_animals with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manasee27/cv_animals with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Manasee27/cv_animals") 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("Manasee27/cv_animals") model = AutoModelForImageClassification.from_pretrained("Manasee27/cv_animals", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afc53c0c0610a2f0151489cfa0fbc8500ec549064f25c59b83d58c6f9d986712
- Size of remote file:
- 343 MB
- SHA256:
- 6a846c0d416a8ca53ff9c1b89c53f9fd8cdd62023b2d8bc2d05e159e6ad69ed9
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