Safetensors
Transformers
English
CountGD
computer-vision
counting
grounding-dino
model_hub_mixin
multi-modal
open-vocabulary
pytorch_model_hub_mixin
Instructions to use nikigoli/CountGD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikigoli/CountGD with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nikigoli/CountGD", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "aux_loss": true, | |
| "dec_pred_bbox_embed_share": true, | |
| "dn_box_noise_scale": 1.0, | |
| "dn_label_noise_ratio": 0.5, | |
| "dn_labelbook_size": 91, | |
| "dn_number": 0, | |
| "iter_update": true, | |
| "max_text_len": 256, | |
| "nheads": 8, | |
| "num_feature_levels": 4, | |
| "num_patterns": 0, | |
| "num_queries": 900, | |
| "query_dim": 4, | |
| "sub_sentence_present": true, | |
| "text_encoder_type": "checkpoints/bert-base-uncased", | |
| "two_stage_bbox_embed_share": false, | |
| "two_stage_class_embed_share": false, | |
| "two_stage_type": "standard" | |
| } |