Instructions to use google/matcha-chart2text-pew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/matcha-chart2text-pew with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="google/matcha-chart2text-pew")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("google/matcha-chart2text-pew") model = AutoModelForImageTextToText.from_pretrained("google/matcha-chart2text-pew") - Notebooks
- Google Colab
- Kaggle
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README.md
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This model is the MatCha model, fine-tuned on Chart2text-pew dataset.
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# Table of Contents
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This model is the MatCha model, fine-tuned on Chart2text-pew dataset. This fine-tuned checkpoint might be better suited for chart summarization task.
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# Table of Contents
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