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README.md
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processor.push_to_hub("USERNAME/MODEL_NAME")
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```
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## Run a prediction
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You can run a prediction by querying an input image together with a question as follows:
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```python
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from transformers import Pix2StructForConditionalGeneration, Pix2StructProcessor
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import requests
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from PIL import Image
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model = Pix2StructForConditionalGeneration.from_pretrained('google/matcha-chartqa')
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processor = Pix2StructProcessor.from_pretrained('google/matcha-chartqa')
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url = "https://raw.githubusercontent.com/vis-nlp/ChartQA/main/ChartQA%20Dataset/val/png/5090.png"
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image = Image.open(requests.get(url, stream=True).raw)
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inputs = processor(images=image, text="Generate underlying data table of the figure below:", return_tensors="pt")
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predictions = model.generate(**inputs, max_new_tokens=512)
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print(processor.decode(predictions[0], skip_special_tokens=True))
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```
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# Contribution
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This model was originally contributed by Fangyu Liu, Francesco Piccinno et al. and added to the Hugging Face ecosystem by [Younes Belkada](https://huggingface.co/ybelkada).
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processor.push_to_hub("USERNAME/MODEL_NAME")
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```
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# Contribution
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This model was originally contributed by Fangyu Liu, Francesco Piccinno et al. and added to the Hugging Face ecosystem by [Younes Belkada](https://huggingface.co/ybelkada).
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