Instructions to use RamzesIII/llmv2-docvqa-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RamzesIII/llmv2-docvqa-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="RamzesIII/llmv2-docvqa-finetuned")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("RamzesIII/llmv2-docvqa-finetuned") model = AutoModelForDocumentQuestionAnswering.from_pretrained("RamzesIII/llmv2-docvqa-finetuned") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
This model is part of student project
Model Details
This model is for Documents QA
- Developed by: [RamzesIII]
- Model type: [Transformer]
- Finetuned from model [optional]: [microsoft/layoutlmv2-base-uncased]
Model Sources [optional]
- Repository: [More Information Needed]
- Paper [optional]: [More Information Needed]
- Demo [optional]: [More Information Needed]
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