Update README.md
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README.md
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Next we provide a convenience function for inference. This function takes the model, processor, question, and images, along with messages and images objects for repeated chat-like interactions with the model.
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```python
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def ask_about_image (model, processor, question, images_input=[], verbatim=False,temperature=0.1,show_image=False,
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system="You are a materials scientist. ",
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max_new_tokens=256, messages=[], images=[], use_Markdown=False):
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images_input=ensure_list(images_input)
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if len (images_input)>0:
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for image in tqdm (images_input) :
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if is_url(image):
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images.append (image)
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if show_image:
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Next we provide a convenience function for inference. This function takes the model, processor, question, and images, along with messages and images objects for repeated chat-like interactions with the model.
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```python
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from transformers.image_utils import load_image
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def is_url_or_filename(val) -> bool:
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# Check if it's a URL
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if isinstance(val, str):
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return True
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def ask_about_image (model, processor, question, images_input=[], verbatim=False,temperature=0.1,show_image=False,
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system="You are a materials scientist. ", show_conversation=True,
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max_new_tokens=256, messages=[], images=[], use_Markdown=False):
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images_input=ensure_list(images_input)
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if len (images_input)>0:
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for image in tqdm (images_input) :
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if is_url(image):
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is_url_or_filename= load_image(image)
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images.append (image)
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if show_image:
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