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
Upload processor
Browse files- tokenizer.json +2 -2
tokenizer.json
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"version": "1.0",
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"strategy": "LongestFirst",
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"direction": "Right",
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"pad_to_multiple_of": null,
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"version": "1.0",
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"truncation": {
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"max_length": 64,
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"strategy": "LongestFirst",
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"stride": 0
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"padding": {
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"Fixed": 64
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"direction": "Right",
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"pad_to_multiple_of": null,
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