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Prompting Vision Language Models (VLMs)

Over the next two exercises, you'll use a multi-modal model to analyze the sentiment of a news article and its corresponding headline image from the BBC News dataset on Hugging Face:

BBC News dataset card

To start, you will prepare a chat template for the model that includes both the image and the news article. The dataset (dataset) and headline image (image) have been loaded.

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Multi-Modal Models with Hugging Face

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Övningsinstruktioner

  • Load the news article content (content) from the datapoint at index 6 in the dataset.
  • Complete the text query to insert content into text_query using f-strings.
  • Add the image and text_query to the chat template, specifying the content type of text_query as "text".

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Testa den här övningen genom att slutföra den här exempelkoden.

# Load the news article content from datapoint 6
content = ____

# Complete the text query
text_query = f"Does the news article have a positive, negative, or neutral impact on championship winning chances: {____}. Provide reasoning."

# Add the text query dictionary to the chat template
chat_template = [
    {
        "role": "user",
        "content": [
            {
                "type": "image",
                "image": ____,
            },
            ____
        ],
    }
]
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