Instructions to use google/matcha-chartqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/matcha-chartqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="google/matcha-chartqa")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("google/matcha-chartqa") model = AutoModelForImageTextToText.from_pretrained("google/matcha-chartqa") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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inference: false
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pipeline_tag: visual-question-answering
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license: apache-2.0
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---
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# Model card for MatCha - fine-tuned on ChartQA
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inference: false
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pipeline_tag: visual-question-answering
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license: apache-2.0
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tags:
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- matcha
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---
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# Model card for MatCha - fine-tuned on ChartQA
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