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/tsconfig.json from mrrobot2610/IDP-Machine-learning: direct link, hf CLI and curl.
- Browser
- Download file 592 Bytes
-
https://huggingface.co/mrrobot2610/IDP-Machine-learning/resolve/main/frontend/tsconfig.json
- Command line
-
hf download hf://mrrobot2610/IDP-Machine-learning/frontend/tsconfig.json
-
curl -L -o tsconfig.json https://huggingface.co/mrrobot2610/IDP-Machine-learning/resolve/main/frontend/tsconfig.json
592 Bytes
| { | |
| "compilerOptions": { | |
| "lib": ["dom", "dom.iterable", "esnext"], | |
| "allowJs": true, | |
| "skipLibCheck": true, | |
| "strict": false, | |
| "noEmit": true, | |
| "incremental": true, | |
| "esModuleInterop": true, | |
| "module": "esnext", | |
| "moduleResolution": "node", | |
| "resolveJsonModule": true, | |
| "isolatedModules": true, | |
| "jsx": "preserve", | |
| "plugins": [ | |
| { | |
| "name": "next" | |
| } | |
| ], | |
| "baseUrl": ".", | |
| "paths": { | |
| "@/*": ["./*"] | |
| } | |
| }, | |
| "include": ["next-env.d.ts", ".next/types/**/*.ts", "**/*.ts", "**/*.tsx"], | |
| "exclude": ["node_modules"] | |
| } | |