Instructions to use TeeA/MATCHA-ChartQA-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeeA/MATCHA-ChartQA-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="TeeA/MATCHA-ChartQA-v1")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("TeeA/MATCHA-ChartQA-v1") model = AutoModelForImageTextToText.from_pretrained("TeeA/MATCHA-ChartQA-v1") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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datasets:
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- TeeA/ChartQA
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library_name: transformers
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pipeline_tag: visual-question-answering
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widget:
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- text: "Một trong những thực phẩm chủ yếu của quốc gia Nam Á này là gì? "
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src: ChartQA-demo.png
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