Instructions to use LiviaQi/trained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiviaQi/trained_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="LiviaQi/trained_model")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("LiviaQi/trained_model") model = AutoModelForObjectDetection.from_pretrained("LiviaQi/trained_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9d850ba6e37968609111aedc245412744807b4fbc85a252e19834114ea19c2c
- Size of remote file:
- 3.9 kB
- SHA256:
- a79b03c0a37c584cdc212de64d7d60a176a486269ecc9fdf28218c74948def01
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