Instructions to use 0llheaven/Conditional-detr-finetuned-tf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 0llheaven/Conditional-detr-finetuned-tf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="0llheaven/Conditional-detr-finetuned-tf")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("0llheaven/Conditional-detr-finetuned-tf") model = AutoModelForObjectDetection.from_pretrained("0llheaven/Conditional-detr-finetuned-tf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18d83a260901ec3fcf9d421b31be1c8b3f3c1bee03e3813f7618efc0a2a91f29
- Size of remote file:
- 174 MB
- SHA256:
- d5e87ca66c4b7caf9d392d7f84ab0b6507eafa23a8aa4bef0273c4f8e497dbe0
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