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
| { | |
| "profile": "model2aa", | |
| "selection_mode": "full_manifest", | |
| "selected_page_count": 28066, | |
| "train_page_count": 25255, | |
| "eval_page_count": 2811, | |
| "label_order": [ | |
| "Visit Note(multiple notes)", | |
| "Progress/Follow up Note" | |
| ], | |
| "label_counts_selected": { | |
| "Progress/Follow up Note": 14033, | |
| "Visit Note(multiple notes)": 14033 | |
| }, | |
| "label_counts_train": { | |
| "Progress/Follow up Note": 12625, | |
| "Visit Note(multiple notes)": 12630 | |
| }, | |
| "label_counts_eval": { | |
| "Progress/Follow up Note": 1408, | |
| "Visit Note(multiple notes)": 1403 | |
| } | |
| } |