Instructions to use brainer/detr-resnet-50-dc5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brainer/detr-resnet-50-dc5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="brainer/detr-resnet-50-dc5")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("brainer/detr-resnet-50-dc5") model = AutoModelForObjectDetection.from_pretrained("brainer/detr-resnet-50-dc5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c51c7bfc41b944fe72778bac890f25530ce091eaff435d29cfa531c45b05453
- Size of remote file:
- 4.6 kB
- SHA256:
- c515995bdbd0d6eae32bdeca02abbc4bef02ff81a5a823d6747fdbb11a01b5f2
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