Text Classification
Transformers
Safetensors
layoutlmv3
document-classification
medical-documents
model2a
Generated from Trainer
Instructions to use neuralit/layoutlmv3-large-model2a-router-2aa-vs-2ab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuralit/layoutlmv3-large-model2a-router-2aa-vs-2ab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="neuralit/layoutlmv3-large-model2a-router-2aa-vs-2ab")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("neuralit/layoutlmv3-large-model2a-router-2aa-vs-2ab") model = AutoModelForSequenceClassification.from_pretrained("neuralit/layoutlmv3-large-model2a-router-2aa-vs-2ab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| split,training_label,source_super_category,page_count | |
| all,Route to Model 2aa,,3000 | |
| all,Route to Model 2ab,,4500 | |
| all,Route to Model 2aa,Progress/Follow up Note,1500 | |
| all,Route to Model 2aa,Visit Note,1500 | |
| all,Route to Model 2ab,Consultation Note,1500 | |
| all,Route to Model 2ab,Discharge Report,1500 | |
| all,Route to Model 2ab,Telephone Encounter,1500 | |
| train,Route to Model 2aa,,2700 | |
| train,Route to Model 2ab,,4048 | |
| train,Route to Model 2aa,Progress/Follow up Note,1350 | |
| train,Route to Model 2aa,Visit Note,1350 | |
| train,Route to Model 2ab,Consultation Note,1349 | |
| train,Route to Model 2ab,Discharge Report,1349 | |
| train,Route to Model 2ab,Telephone Encounter,1350 | |
| eval,Route to Model 2aa,,300 | |
| eval,Route to Model 2ab,,452 | |
| eval,Route to Model 2aa,Progress/Follow up Note,150 | |
| eval,Route to Model 2aa,Visit Note,150 | |
| eval,Route to Model 2ab,Consultation Note,151 | |
| eval,Route to Model 2ab,Discharge Report,151 | |
| eval,Route to Model 2ab,Telephone Encounter,150 | |