Instructions to use faisalraza/layoutlm-invoices with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faisalraza/layoutlm-invoices with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="faisalraza/layoutlm-invoices")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForDocumentQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("faisalraza/layoutlm-invoices") model = AutoModelForDocumentQuestionAnswering.from_pretrained("faisalraza/layoutlm-invoices", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from faisalraza/layoutlm-invoices: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
-
https://huggingface.co/faisalraza/layoutlm-invoices/resolve/main/tokenizer.json
- Command line
-
hf download hf://faisalraza/layoutlm-invoices/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/faisalraza/layoutlm-invoices/resolve/main/tokenizer.json
1.36 MB
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