Instructions to use SvNext/GambleTestDETR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SvNext/GambleTestDETR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SvNext/GambleTestDETR")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("SvNext/GambleTestDETR") model = AutoModelForObjectDetection.from_pretrained("SvNext/GambleTestDETR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from SvNext/GambleTestDETR: direct link, hf CLI and curl.
- Browser
- Download file 1.24 kB
-
https://huggingface.co/SvNext/GambleTestDETR/resolve/refs%2Fpr%2F2/config.json
- Command line
-
hf download hf://SvNext/GambleTestDETR@refs/pr/2/config.json
-
curl -L -o config.json https://huggingface.co/SvNext/GambleTestDETR/resolve/refs%2Fpr%2F2/config.json
1.24 kB
| { | |
| "_commit_hash": "480370a8aeeed9fc8d78837b4e94e5f936fe73f2", | |
| "_name_or_path": "facebook/detr-resnet-50", | |
| "activation_dropout": 0.0, | |
| "activation_function": "relu", | |
| "architectures": [ | |
| "DetrForObjectDetection" | |
| ], | |
| "attention_dropout": 0.0, | |
| "auxiliary_loss": false, | |
| "backbone": "resnet50", | |
| "backbone_config": null, | |
| "bbox_cost": 5, | |
| "bbox_loss_coefficient": 5, | |
| "class_cost": 1, | |
| "classifier_dropout": 0.0, | |
| "d_model": 256, | |
| "decoder_attention_heads": 8, | |
| "decoder_ffn_dim": 2048, | |
| "decoder_layerdrop": 0.0, | |
| "decoder_layers": 6, | |
| "dice_loss_coefficient": 1, | |
| "dilation": false, | |
| "dropout": 0.1, | |
| "encoder_attention_heads": 8, | |
| "encoder_ffn_dim": 2048, | |
| "encoder_layerdrop": 0.0, | |
| "encoder_layers": 6, | |
| "eos_coefficient": 0.1, | |
| "giou_cost": 2, | |
| "giou_loss_coefficient": 2, | |
| "init_std": 0.02, | |
| "init_xavier_std": 1.0, | |
| "is_encoder_decoder": true, | |
| "mask_loss_coefficient": 1, | |
| "max_position_embeddings": 1024, | |
| "model_type": "detr", | |
| "num_channels": 3, | |
| "num_hidden_layers": 6, | |
| "num_queries": 100, | |
| "position_embedding_type": "sine", | |
| "scale_embedding": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.7.0.dev0", | |
| "use_pretrained_backbone": true, | |
| "use_timm_backbone": true | |
| } | |