Instructions to use TeeA/MATCHA-ViChart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeeA/MATCHA-ViChart with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="TeeA/MATCHA-ViChart")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("TeeA/MATCHA-ViChart") model = AutoModelForImageTextToText.from_pretrained("TeeA/MATCHA-ViChart") - Notebooks
- Google Colab
- Kaggle
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README.md
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metrics:
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- accuracy
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pipeline_tag: visual-question-answering
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widget:
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src: "
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- text: "Where is it?"
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src: "https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg"
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---
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metrics:
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- accuracy
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pipeline_tag: visual-question-answering
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tags:
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- vision
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model_name: TeeA/MATCHA-ViChart
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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: "image.png"
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