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You can use these models as follows (example on a ChatQA dataset): thon from transformers import AutoProcessor, Pix2StructForConditionalGeneration import requests from PIL import Image model = Pix2StructForConditionalGeneration.from_pretrained("google/matcha-chartqa").to(0) processor = AutoProcessor.from_pretrained("google/matcha-chartqa") url = "https://raw.githubusercontent.com/vis-nlp/ChartQA/main/ChartQA%20Dataset/val/png/20294671002019.png" image = Image.open(requests.get(url, stream=True).raw) inputs = processor(images=image, text="Is the sum of all 4 places greater than Laos? |