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Upload README.md with huggingface_hub

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  ---
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  inference: false
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- pipeline_tag: visual-question-answering
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  ---
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  <br>
@@ -54,7 +53,20 @@ predictor = huggingface_model.deploy(
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  instance_type="ml.g5.xlarge",
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  )
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  ```
 
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  ## License
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  Llama 2 is licensed under the LLAMA 2 Community License,
 
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  ---
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  inference: false
 
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  ---
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  <br>
 
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  instance_type="ml.g5.xlarge",
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  )
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  ```
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+ ## Inference on SageMaker
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+ ```python
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+ data = {
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+ "image" : 'https://raw.githubusercontent.com/haotian-liu/LLaVA/main/images/llava_logo.png',
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+ "question" : "Describe the image and color details.",
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+ # "max_new_tokens" : 1024,
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+ # "temperature" : 0.2,
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+ # "conv_mode" : "llava_v1"
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+ }
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+ output = predictor.predict(data)
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+ print(output)
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+ ```
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+ Or use [SageMakerRuntime](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker-runtime/client/invoke_endpoint.html#invoke-endpoint) to setup endpoint invoking client.
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  ## License
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  Llama 2 is licensed under the LLAMA 2 Community License,