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:
- 98f96e41a5565361dbaed0083be222d12bec6a0fdd0863e64faf7e138b89ff7c
- Size of remote file:
- 3.9 kB
- SHA256:
- eeb17050d6aa6f89ada02c71b933c4c555247418b5a1c495fa8b90c1848ff599
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