Instructions to use JuncalG/practica_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JuncalG/practica_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="JuncalG/practica_2")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("JuncalG/practica_2") model = AutoModelForObjectDetection.from_pretrained("JuncalG/practica_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b14fbdf5d4fe7557536f5b1209133d2769d0ac4d1a7adbc1dff0811d90269aa5
- Size of remote file:
- 5.24 kB
- SHA256:
- 3477806a4b71844efa05e22d9f88db5c915068aa082febc43f933320ee33026a
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