Object Detection
Transformers
Safetensors
rt_detr_v2
document-layout-analysis
finance
rtdetr-v2
cuda
tf32
Instructions to use AutomatosX/AXDocLayout-M-v1.5-CUDA-TF32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AutomatosX/AXDocLayout-M-v1.5-CUDA-TF32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="AutomatosX/AXDocLayout-M-v1.5-CUDA-TF32")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForObjectDetection tokenizer = AutoTokenizer.from_pretrained("AutomatosX/AXDocLayout-M-v1.5-CUDA-TF32") model = AutoModelForObjectDetection.from_pretrained("AutomatosX/AXDocLayout-M-v1.5-CUDA-TF32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 3,263 Bytes
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"activation_dropout": 0.0,
"activation_function": "silu",
"anchor_image_size": null,
"architectures": [
"RTDetrV2ForObjectDetection"
],
"attention_dropout": 0.0,
"auxiliary_loss": true,
"backbone": null,
"backbone_config": {
"depths": [
3,
4,
6,
3
],
"downsample_in_bottleneck": false,
"downsample_in_first_stage": false,
"embedding_size": 64,
"hidden_act": "relu",
"hidden_sizes": [
256,
512,
1024,
2048
],
"layer_type": "bottleneck",
"model_type": "rt_detr_resnet",
"num_channels": 3,
"out_features": [
"stage2",
"stage3",
"stage4"
],
"out_indices": [
2,
3,
4
],
"stage_names": [
"stem",
"stage1",
"stage2",
"stage3",
"stage4"
]
},
"backbone_kwargs": null,
"batch_norm_eps": 1e-05,
"box_noise_scale": 1.0,
"d_model": 256,
"decoder_activation_function": "relu",
"decoder_attention_heads": 8,
"decoder_ffn_dim": 1024,
"decoder_in_channels": [
256,
256,
256
],
"decoder_layers": 6,
"decoder_method": "default",
"decoder_n_levels": 3,
"decoder_n_points": 4,
"decoder_offset_scale": 0.5,
"dropout": 0.0,
"encode_proj_layers": [
2
],
"encoder_activation_function": "gelu",
"encoder_attention_heads": 8,
"encoder_ffn_dim": 1024,
"encoder_hidden_dim": 256,
"encoder_in_channels": [
512,
1024,
2048
],
"encoder_layers": 1,
"eos_coefficient": 0.0001,
"eval_size": null,
"feat_strides": [
8,
16,
32
],
"focal_loss_alpha": 0.75,
"focal_loss_gamma": 2.0,
"freeze_backbone_batch_norms": true,
"hidden_expansion": 1.0,
"id2label": {
"0": "caption",
"1": "footnote",
"2": "formula",
"3": "list_item",
"4": "page_footer",
"5": "page_header",
"6": "picture",
"7": "section_header",
"8": "table",
"9": "text",
"10": "title",
"11": "document_index",
"12": "code",
"13": "checkbox_selected",
"14": "checkbox_unselected",
"15": "form",
"16": "key_value_region"
},
"initializer_bias_prior_prob": null,
"initializer_range": 0.01,
"is_encoder_decoder": true,
"label2id": {
"caption": 0,
"checkbox_selected": 13,
"checkbox_unselected": 14,
"code": 12,
"document_index": 11,
"footnote": 1,
"form": 15,
"formula": 2,
"key_value_region": 16,
"list_item": 3,
"page_footer": 4,
"page_header": 5,
"picture": 6,
"section_header": 7,
"table": 8,
"text": 9,
"title": 10
},
"label_noise_ratio": 0.5,
"layer_norm_eps": 1e-05,
"learn_initial_query": false,
"matcher_alpha": 0.25,
"matcher_bbox_cost": 5.0,
"matcher_class_cost": 2.0,
"matcher_gamma": 2.0,
"matcher_giou_cost": 2.0,
"model_type": "rt_detr_v2",
"normalize_before": false,
"num_denoising": 100,
"num_feature_levels": 3,
"num_queries": 300,
"positional_encoding_temperature": 10000,
"torch_dtype": "float32",
"transformers_version": "4.53.3",
"use_focal_loss": true,
"use_pretrained_backbone": false,
"use_timm_backbone": false,
"weight_loss_bbox": 5.0,
"weight_loss_giou": 2.0,
"weight_loss_vfl": 1.0,
"with_box_refine": true
}
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