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@@ -36,4 +36,41 @@ Prometheus-Vision is the first open-source VLM specialized for evaluation purpos
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  Prometheu-Vision is trained with two different sizes (7B and 13B).
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  You could check the 7B sized LM on [this page](https://huggingface.co/kaist-ai/prometheus-vision-7b-v1.0).
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- Also, check out our dataset as well on [this page](https://huggingface.co/datasets/kaist-ai/Perception-Collection).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  Prometheu-Vision is trained with two different sizes (7B and 13B).
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  You could check the 7B sized LM on [this page](https://huggingface.co/kaist-ai/prometheus-vision-7b-v1.0).
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+ Also, check out our dataset as well on [this page](https://huggingface.co/datasets/kaist-ai/Perception-Collection).
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+ ## Prompt Format
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+ Prometheus-Vision requires 5 components in the input: An image, an instruction, a response to evaluate, a score rubric, and a reference answer. You could refer to the prompt format below.
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+ You should fill in the instruction, response, reference answer, criteria description, and score description for score in range of 1 to 5.
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+ ```
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+ ###Task Description:
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+ An instruction (might include an Input inside it), a response to evaluate, a reference answer that gets a score of 5, an image and a score rubric representing an evaluation criterion is given.
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+ 1. Write a detailed feedback that assess the quality of the response strictly based on the given score rubric, not evaluating in general.
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+ 2. After writing a feedback, write a score that is an integer between 1 and 5. You should refer to the score rubric.
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+ 3. The output format should look as follows: \"Feedback: (write a feedback for criteria) [RESULT] (an integer number between 1 and 5)\"
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+ 4. Please do not generate any other opening, closing, and explanations.
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+
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+ ###The instruction to evaluate:
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+ {instruction}
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+
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+ ###Response to evaluate:
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+ {response}
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+
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+ ###Reference Answer (Score 5):
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+ {reference_answer}
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+
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+ ###Score Rubrics:
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+ [{criteria_description}]
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+ Score 1: {score1_description}
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+ Score 2: {score2_description}
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+ Score 3: {score3_description}
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+ Score 4: {score4_description}
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+ Score 5: {score5_description}
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+
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+ ###Feedback:
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+ ```
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+ Also, we use the following output format. During inference, you could parse the score by splitting the number that is generated next to the [RESULT] phrase.
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+ ```
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+ {orig_feedback}
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+ [RESULT] {orig_score}
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+ ```
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+ ## License
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+ Perception Collection and Prometheus-Vision are subject to OpenAI's Terms of Use for the generated data. If you suspect any violations, please reach out to us.