Instructions to use dhruvindankhara/DETR_FineTuning_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhruvindankhara/DETR_FineTuning_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="dhruvindankhara/DETR_FineTuning_3")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("dhruvindankhara/DETR_FineTuning_3") model = AutoModelForObjectDetection.from_pretrained("dhruvindankhara/DETR_FineTuning_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85f7f48e8fbbf4c95a99fbc937674947e14faf379d59f84e563090737d9f8aa3
- Size of remote file:
- 167 MB
- SHA256:
- 949d355ee2c46c9997feef73c3b163ca3d95c17344c03376b964975a689295c3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.