Instructions to use aaa950739/trained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aaa950739/trained_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="aaa950739/trained_model")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("aaa950739/trained_model") model = AutoModelForObjectDetection.from_pretrained("aaa950739/trained_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c209f001fa7d17a9e01338faa78fa46058e426e50b0756e001453a1ae541c1c
- Size of remote file:
- 3.9 kB
- SHA256:
- 136fb482f4109a9409b8d3b9a53d6d7b48559cd176b18763f2dd6923614056af
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