Instructions to use vaibhav1411/layoutlmv2-finetuned-cord with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vaibhav1411/layoutlmv2-finetuned-cord with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vaibhav1411/layoutlmv2-finetuned-cord")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("vaibhav1411/layoutlmv2-finetuned-cord") model = AutoModelForTokenClassification.from_pretrained("vaibhav1411/layoutlmv2-finetuned-cord") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "microsoft/layoutlmv2-large-uncased", | |
| "architectures": [ | |
| "LayoutLMv2ForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "convert_sync_batchnorm": true, | |
| "coordinate_size": 171, | |
| "detectron2_config_args": { | |
| "MODEL.ANCHOR_GENERATOR.SIZES": [ | |
| [ | |
| 32 | |
| ], | |
| [ | |
| 64 | |
| ], | |
| [ | |
| 128 | |
| ], | |
| [ | |
| 256 | |
| ], | |
| [ | |
| 512 | |
| ] | |
| ], | |
| "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone", | |
| "MODEL.FPN.IN_FEATURES": [ | |
| "res2", | |
| "res3", | |
| "res4", | |
| "res5" | |
| ], | |
| "MODEL.MASK_ON": true, | |
| "MODEL.PIXEL_STD": [ | |
| 57.375, | |
| 57.12, | |
| 58.395 | |
| ], | |
| "MODEL.POST_NMS_TOPK_TEST": 1000, | |
| "MODEL.RESNETS.ASPECT_RATIOS": [ | |
| [ | |
| 0.5, | |
| 1.0, | |
| 2.0 | |
| ] | |
| ], | |
| "MODEL.RESNETS.DEPTH": 101, | |
| "MODEL.RESNETS.NUM_GROUPS": 32, | |
| "MODEL.RESNETS.OUT_FEATURES": [ | |
| "res2", | |
| "res3", | |
| "res4", | |
| "res5" | |
| ], | |
| "MODEL.RESNETS.SIZES": [ | |
| [ | |
| 32 | |
| ], | |
| [ | |
| 64 | |
| ], | |
| [ | |
| 128 | |
| ], | |
| [ | |
| 256 | |
| ], | |
| [ | |
| 512 | |
| ] | |
| ], | |
| "MODEL.RESNETS.STRIDE_IN_1X1": false, | |
| "MODEL.RESNETS.WIDTH_PER_GROUP": 8, | |
| "MODEL.ROI_BOX_HEAD.NAME": "FastRCNNConvFCHead", | |
| "MODEL.ROI_BOX_HEAD.NUM_FC": 2, | |
| "MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION": 14, | |
| "MODEL.ROI_HEADS.IN_FEATURES": [ | |
| "p2", | |
| "p3", | |
| "p4", | |
| "p5" | |
| ], | |
| "MODEL.ROI_HEADS.NAME": "StandardROIHeads", | |
| "MODEL.ROI_HEADS.NUM_CLASSES": 5, | |
| "MODEL.ROI_MASK_HEAD.NAME": "MaskRCNNConvUpsampleHead", | |
| "MODEL.ROI_MASK_HEAD.NUM_CONV": 4, | |
| "MODEL.ROI_MASK_HEAD.POOLER_RESOLUTION": 7, | |
| "MODEL.RPN.IN_FEATURES": [ | |
| "p2", | |
| "p3", | |
| "p4", | |
| "p5", | |
| "p6" | |
| ], | |
| "MODEL.RPN.POST_NMS_TOPK_TRAIN": 1000, | |
| "MODEL.RPN.PRE_NMS_TOPK_TEST": 1000, | |
| "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 2000 | |
| }, | |
| "fast_qkv": false, | |
| "gradient_checkpointing": false, | |
| "has_relative_attention_bias": true, | |
| "has_spatial_attention_bias": true, | |
| "has_visual_segment_embedding": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "I-others", | |
| "1": "I-password", | |
| "2": "I-mobile number", | |
| "3": "I-name", | |
| "4": "I-email id", | |
| "5": "I-address", | |
| "6": "I-date", | |
| "7": "I-user id", | |
| "8": "I-username", | |
| "9": "I-zipcode", | |
| "10": "I-amount", | |
| "11": "I-gps coordinates", | |
| "12": "I-OTP", | |
| "13": "I-pin", | |
| "14": "I-account number", | |
| "15": "I-social security number", | |
| "16": "I-transaction id", | |
| "17": "I-time" | |
| }, | |
| "image_feature_pool_shape": [ | |
| 7, | |
| 7, | |
| 256 | |
| ], | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "I-OTP": 12, | |
| "I-account number": 14, | |
| "I-address": 5, | |
| "I-amount": 10, | |
| "I-date": 6, | |
| "I-email id": 4, | |
| "I-gps coordinates": 11, | |
| "I-mobile number": 2, | |
| "I-name": 3, | |
| "I-others": 0, | |
| "I-password": 1, | |
| "I-pin": 13, | |
| "I-social security number": 15, | |
| "I-time": 17, | |
| "I-transaction id": 16, | |
| "I-user id": 7, | |
| "I-username": 8, | |
| "I-zipcode": 9 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_2d_position_embeddings": 1024, | |
| "max_position_embeddings": 512, | |
| "max_rel_2d_pos": 256, | |
| "max_rel_pos": 128, | |
| "model_type": "layoutlmv2", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "rel_2d_pos_bins": 64, | |
| "rel_pos_bins": 32, | |
| "shape_size": 170, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.42.3", | |
| "type_vocab_size": 2, | |
| "vocab_size": 30522 | |
| } | |