Object Detection
Transformers
Safetensors
English
rf_detr
text-generation-inference
mobile-gui-detection
Instructions to use prithivMLmods/rf-detr-mobile-gui-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/rf-detr-mobile-gui-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="prithivMLmods/rf-detr-mobile-gui-detection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("prithivMLmods/rf-detr-mobile-gui-detection") model = AutoModelForObjectDetection.from_pretrained("prithivMLmods/rf-detr-mobile-gui-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 2,586 Bytes
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"activation_dropout": 0.0,
"activation_function": "silu",
"architectures": [
"RfDetrForObjectDetection"
],
"attention_bias": true,
"attention_dropout": 0.0,
"auxiliary_loss": true,
"backbone_config": {
"apply_layernorm": true,
"attention_probs_dropout_prob": 0.0,
"drop_path_rate": 0.0,
"dtype": "float32",
"hidden_act": "gelu",
"hidden_dropout_prob": 0.0,
"hidden_size": 384,
"image_size": 576,
"initializer_range": 0.02,
"layer_norm_eps": 1e-06,
"layerscale_value": 1.0,
"mlp_ratio": 4,
"model_type": "rf_detr_dinov2",
"num_attention_heads": 6,
"num_channels": 3,
"num_hidden_layers": 12,
"num_windows": 2,
"out_features": [
"stage3",
"stage6",
"stage9",
"stage12"
],
"out_indices": [
3,
6,
9,
12
],
"patch_size": 16,
"qkv_bias": true,
"reshape_hidden_states": true,
"stage_names": [
"stem",
"stage1",
"stage2",
"stage3",
"stage4",
"stage5",
"stage6",
"stage7",
"stage8",
"stage9",
"stage10",
"stage11",
"stage12"
],
"use_mask_token": true,
"use_swiglu_ffn": false,
"window_block_indexes": [
0,
1,
2,
4,
5,
7,
8,
10,
11
]
},
"bbox_cost": 5,
"bbox_loss_coefficient": 5,
"c2f_num_blocks": 3,
"class_cost": 2,
"class_loss_coefficient": 1,
"d_model": 256,
"decoder_activation_function": "relu",
"decoder_cross_attention_heads": 16,
"decoder_ffn_dim": 2048,
"decoder_layers": 4,
"decoder_n_points": 2,
"decoder_self_attention_heads": 8,
"dice_loss_coefficient": 1,
"disable_custom_kernels": true,
"dropout": 0.1,
"dtype": "float32",
"eos_coefficient": 0.1,
"focal_alpha": 0.25,
"giou_cost": 2,
"giou_loss_coefficient": 2,
"group_detr": 13,
"hidden_expansion": 0.5,
"id2label": {
"0": "group",
"1": "image",
"2": "rectangle",
"3": "text"
},
"init_std": 0.02,
"intermediate_size": 1024,
"label2id": {
"group": 0,
"image": 1,
"rectangle": 2,
"text": 3
},
"layer_norm_eps": 1e-05,
"mask_class_loss_coefficient": 5.0,
"mask_dice_loss_coefficient": 5.0,
"mask_downsample_ratio": 4,
"mask_loss_coefficient": 1,
"mask_point_sample_ratio": 16,
"model_type": "rf_detr",
"num_feature_levels": 1,
"num_queries": 300,
"projector_scale_factors": [
1.0
],
"segmentation_head_activation_function": "gelu",
"transformers_version": "5.12.1",
"use_cache": false
}
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