Update README.md

README.md

@@ -6,7 +6,58 @@ tags: []
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
-
+## Code to create model
+```python
+import torch
+from transformers import GroundingDinoConfig, GroundingDinoForObjectDetection, AutoProcessor
+
+model_id = 'IDEA-Research/grounding-dino-tiny'
+config = GroundingDinoConfig.from_pretrained(
+    model_id,
+    decoder_layers=1,
+    decoder_attention_heads=2,
+    encoder_layers=1,
+    encoder_attention_heads=2,
+    text_config=dict(
+        num_attention_heads=2,
+        num_hidden_layers=1,
+        hidden_size=32,
+    ),
+    backbone_config=dict(
+        attention_probs_dropout_prob=0.0,
+        depths=[1, 1, 2, 1],
+        drop_path_rate=0.1,
+        embed_dim=12,
+        encoder_stride=32,
+        hidden_act="gelu",
+        hidden_dropout_prob=0.0,
+        hidden_size=48,
+        image_size=224,
+        initializer_range=0.02,
+        layer_norm_eps=1e-05,
+        mlp_ratio=4.0,
+        num_channels=3,
+        num_heads=[1, 2, 3, 4],
+        num_layers=4,
+        out_features=["stage2", "stage3", "stage4"],
+        out_indices=[2, 3, 4],
+        patch_size=4,
+        stage_names=["stem", "stage1", "stage2", "stage3", "stage4"],
+        window_size=7
+    )
+)
+
+# Create model and randomize all weights
+model = GroundingDinoForObjectDetection(config)
+
+torch.manual_seed(0) # Set for reproducibility
+for name, param in model.named_parameters():
+    param.data = torch.randn_like(param)
+
+processor = AutoProcessor.from_pretrained(model_id)
+
+print(model.num_parameters())  # 7751525
+```
 
 
 ## Model Details