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
File size: 954 Bytes
4da0101 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | 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
|