Instructions to use Thastp/rf-detr-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Thastp/rf-detr-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Thastp/rf-detr-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForObjectDetection model = AutoModelForObjectDetection.from_pretrained("Thastp/rf-detr-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "auto_map": { | |
| "AutoImageProcessor": "image_processing_rf_detr.RFDetrImageProcessor" | |
| }, | |
| "config": { | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ] | |
| }, | |
| "image_processor_type": "RFDetrImageProcessor", | |
| "model_name": "RFDETRBase", | |
| "post_process_config": { | |
| "num_select": 300 | |
| } | |
| } | |