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
Download frontend/next-env.d.ts from mrrobot2610/IDP-Machine-learning: direct link, hf CLI and curl.
- Browser
- Download file 206 Bytes
-
https://huggingface.co/mrrobot2610/IDP-Machine-learning/resolve/main/frontend/next-env.d.ts
- Command line
-
hf download hf://mrrobot2610/IDP-Machine-learning/frontend/next-env.d.ts
-
curl -L -o next-env.d.ts https://huggingface.co/mrrobot2610/IDP-Machine-learning/resolve/main/frontend/next-env.d.ts
206 Bytes
| /// <reference types="next" /> | |
| /// <reference types="next/image-types/global" /> | |
| // NOTE: This file should not be edited | |
| // see https://nextjs.org/docs/basic-features/typescript for more information. | |