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xgen-mm-phi3-mini-instruct-r-v1

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tokenizer.padding_side = "left"

#Adding one more img in the list
inputs = image_processor([img, img], return_tensors="pt", image_aspect_ratio='anyres') # image_aspect_ratio='anyres')

prompt = apply_prompt_template(sample['question'])
language_inputs = tokenizer([prompt], return_tensors="pt")
inputs.update(language_inputs)

#Batch size becomes 2
torch.Size([1, 2, 5, 3, 378, 378])

RuntimeError: Expected 3D (unbatched) or 4D (batched) input to conv2d, but got input of size: [2, 5, 3, 378, 378]

@Napron Thanks for your interest in our work. We will work on it and update you when the batch inference feature is ready.

Hi @Napron , thank you for being patient. Check out our latest notebook for batch inference. Let us know if you have any questions.

Thank you, appreciate it!