Text Classification
Transformers
Safetensors
layoutlmv3
document-classification
medical-documents
model2aa
Generated from Trainer
Instructions to use neuralit/layoutlmv3-large-model2aa-visit-vs-progress with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuralit/layoutlmv3-large-model2aa-visit-vs-progress with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="neuralit/layoutlmv3-large-model2aa-visit-vs-progress")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("neuralit/layoutlmv3-large-model2aa-visit-vs-progress") model = AutoModelForSequenceClassification.from_pretrained("neuralit/layoutlmv3-large-model2aa-visit-vs-progress") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "LayoutLMv3ForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "coordinate_size": 171, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "has_relative_attention_bias": true, | |
| "has_spatial_attention_bias": true, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "Visit Note(multiple notes)", | |
| "1": "Progress/Follow up Note" | |
| }, | |
| "initializer_range": 0.02, | |
| "input_size": 224, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "Progress/Follow up Note": 1, | |
| "Visit Note(multiple notes)": 0 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_2d_position_embeddings": 1024, | |
| "max_position_embeddings": 514, | |
| "max_rel_2d_pos": 256, | |
| "max_rel_pos": 128, | |
| "model_type": "layoutlmv3", | |
| "num_attention_heads": 16, | |
| "num_channels": 3, | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 1, | |
| "patch_size": 16, | |
| "problem_type": "single_label_classification", | |
| "rel_2d_pos_bins": 64, | |
| "rel_pos_bins": 32, | |
| "second_input_size": 112, | |
| "shape_size": 170, | |
| "text_embed": true, | |
| "transformers_version": "4.57.6", | |
| "type_vocab_size": 1, | |
| "visual_embed": true, | |
| "vocab_size": 50265 | |
| } | |