keras/medsiglip_900m_448

This is a SigLIP model uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends. Model config:

• name: sig_lip_backbone
• trainable: True
• dtype: {'module': 'keras', 'class_name': 'DTypePolicy', 'config': {'name': 'float32'}, 'registered_name': None}
• vision_encoder: {'module': 'keras_hub.src.models.siglip.siglip_vision_encoder', 'class_name': 'SigLIPVisionEncoder', 'config': {'name': 'sig_lip_vision_encoder', 'trainable': True, 'dtype': {'module': 'keras', 'class_name': 'DTypePolicy', 'config': {'name': 'float32'}, 'registered_name': None}, 'patch_size': 14, 'hidden_dim': 1152, 'num_layers': 27, 'num_heads': 16, 'intermediate_dim': 4304, 'intermediate_activation': 'gelu_approximate', 'layer_norm_epsilon': 1e-06, 'image_shape': [448, 448, 3]}, 'registered_name': 'keras_hub>SigLIPVisionEncoder'}
• text_encoder: {'module': 'keras_hub.src.models.siglip.siglip_text_encoder', 'class_name': 'SigLIPTextEncoder', 'config': {'name': 'sig_lip_text_encoder', 'trainable': True, 'dtype': {'module': 'keras', 'class_name': 'DTypePolicy', 'config': {'name': 'float32'}, 'registered_name': None}, 'vocabulary_size': 32000, 'embedding_dim': 1152, 'hidden_dim': 1152, 'num_layers': 27, 'num_heads': 16, 'intermediate_dim': 4304, 'intermediate_activation': 'gelu_approximate', 'layer_norm_epsilon': 1e-06, 'max_sequence_length': 64, 'projection_dim': 1152}, 'registered_name': 'keras_hub>SigLIPTextEncoder'}

This model card has been generated automatically and should be completed by the model author. See Model Cards documentation for more information.