Instructions to use magarcd/practica_2_kangaroo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magarcd/practica_2_kangaroo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="magarcd/practica_2_kangaroo")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("magarcd/practica_2_kangaroo") model = AutoModelForObjectDetection.from_pretrained("magarcd/practica_2_kangaroo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ea51e3c7360cf108de6ca3d8e7ffe97ec88767721b3db312eba5a2a308f6bb4
- Size of remote file:
- 5.3 kB
- SHA256:
- 300f04ae519018652b6ecdcee53dc7b88d11a86dc4573b7276915550237d8fda
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