Document Question Answering
Transformers
PyTorch
English
document-processing
ocr
ner
text-classification
information-extraction
invoice
receipt
form
Instructions to use mrrobot2610/IDP-Machine-learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrrobot2610/IDP-Machine-learning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="mrrobot2610/IDP-Machine-learning")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrrobot2610/IDP-Machine-learning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 298 Bytes
1a7ee60 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"model_name": "nreimers/MiniLM-L6-H384-uncased",
"num_labels": 4,
"label2id": {
"INVOICE": 0,
"RECEIPT": 1,
"FORM": 2,
"OTHER": 3
},
"id2label": {
"0": "INVOICE",
"1": "RECEIPT",
"2": "FORM",
"3": "OTHER"
},
"best_val_accuracy": 1.0
} |