Instructions to use google/matcha-plotqa-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/matcha-plotqa-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="google/matcha-plotqa-v1")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("google/matcha-plotqa-v1") model = AutoModelForMultimodalLM.from_pretrained("google/matcha-plotqa-v1") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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# Model card for MatCha - fine-tuned on
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This model is the MatCha model, fine-tuned on
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# Table of Contents
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license: apache-2.0
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# Model card for MatCha - fine-tuned on PlotQA-v1 dataset
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This model is the MatCha model, fine-tuned on plotQA-v1 dataset. This fine-tuned checkpoint might be better suited for plots question answering tasks.
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# Table of Contents
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