Object Detection
PyTorch
TensorBoard
ONNX
Safetensors
Transformers
English
d_fine
feature-extraction
AgTech
custom_code
Eval Results (legacy)
Instructions to use Laudando-Associates-LLC/d-fine-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Laudando-Associates-LLC/d-fine-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Laudando-Associates-LLC/d-fine-medium", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Laudando-Associates-LLC/d-fine-medium", trust_remote_code=True) model = AutoModel.from_pretrained("Laudando-Associates-LLC/d-fine-medium", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "d_fine", | |
| "architectures": ["DFineModel"], | |
| "auto_map": { | |
| "AutoConfig": "Laudando-Associates-LLC/d-fine-medium--configuration_dfine.DFineConfig", | |
| "AutoModel": "Laudando-Associates-LLC/d-fine-medium--modeling_dfine.DFineModel" | |
| }, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.51.3", | |
| "input_size": [640, 640], | |
| "input_components": ["images", "orig_target_sizes", "ratio", "pad_w", "pad_h"], | |
| "output_components": ["labels", "boxes", "scores"] | |
| } |