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@@ -23,7 +23,7 @@ Phi-3 Vision is a lightweight, state-of-the-art open multimodal model built upon
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  Resources and Technical Documentation:
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- + [Phi-3 Microsoft Blog](https://aka.ms/phi3blog-april)
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  + [Phi-3 Technical Report](https://aka.ms/phi3-tech-report)
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  + [Phi-3 on Azure AI Studio](https://aka.ms/phi3-azure-ai)
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@@ -79,7 +79,7 @@ Phi-3-Vision-128K-Instruct is also available in [Azure AI Studio](https://aka.ms
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  ### Chat Format
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- Given the nature of the training data, the Phi-3-Vision-128K-Instruct model is best suited for prompts using the chat format as follows.
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  You can provide the prompt as a single image with a generic template as follow:
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  ```markdown
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  <|user|>\n<|image_1|>\n{prompt}<|end|>\n<|assistant|>\n
@@ -135,7 +135,7 @@ response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_
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  print(response)
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  ```
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- Additional basic examples are provided [here](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct/resolve/main/sample_inference.py.py).
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  ## Responsible AI Considerations
 
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  Resources and Technical Documentation:
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+ + [Phi-3 Microsoft Blog](https://aka.ms/Phi-3Build2024)
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  + [Phi-3 Technical Report](https://aka.ms/phi3-tech-report)
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  + [Phi-3 on Azure AI Studio](https://aka.ms/phi3-azure-ai)
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  ### Chat Format
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+ Given the nature of the training data, the Phi-3-Vision-128K-Instruct model is best suited for a single image input wih prompts using the chat format as follows.
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  You can provide the prompt as a single image with a generic template as follow:
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  ```markdown
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  <|user|>\n<|image_1|>\n{prompt}<|end|>\n<|assistant|>\n
 
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  print(response)
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  ```
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+ Additional basic examples are provided [here](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct/blob/main/sample_inference.py).
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  ## Responsible AI Considerations