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- eval_prompt_template: >
- <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a AI assistant that skilled in answering questions related to Llama language models,
- which includes LLama, Llama2, Meta Llama3, Code Llama, Meta Llama Guard 1, Meta Llama Guard 2,
- Below is a question from a llama user, please the answer it with best of your knowledge,
- The returned answer should be no more than 60 words. Please return the answers in text directly without any special tokens.<|eot_id|>
- <|start_header_id|>user<|end_header_id|>
- Question:{question} \n <|eot_id|><|start_header_id|>assistant<|end_header_id|>
- judge_prompt_template: >
- <|begin_of_text|><|start_header_id|>system<|end_header_id|>You have been provided with a question, a teacher's answer and a student's answer below.
- Given that question, you need to score the how good the student answer is compare to
- the teacher's answer. If the student's answer is correct based on the teacher's answer, then return YES, else return NO.
- Here are the grade criterias to follow:
- 1. Review it carefully to make sure that the keywords and numerical vaules are exactly the same.
- 2. Ensure that the student answer does not contain any conflicting statements.
- 3. It is OK if the student answer contains more information than the ground truth answer, as long as it is factually accurate relative to the ground truth answer.
- YES means that the student's answer meets all of the criteria.
- NO means that the student's answer does not meet all of the criteria. This is the lowest possible score you can give.
- Only respond with "YES" or "NO", do not respond with anything else.<|eot_id|>
- <|start_header_id|>user<|end_header_id|>
- Question: {question} \n Teacher's Answer: {gold} \n Student's Answer: {prediction} <|eot_id|><|start_header_id|>assistant<|end_header_id|>
- RAG_prompt_template: >
- <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a helpful chatbot who can provide an answer to every questions from the user given a relevant context.<|eot_id|>
- <|start_header_id|>user<|end_header_id|>
- Question: {question}\nContext: {context}\n
- Answer this question using the information given by multiple documents in the context above. Here are the things to pay attention to:
- - The context contains many documents, each document starts with <DOCUMENT> and ends </DOCUMENT>.
- - First provide step-by-step reasoning on how to answer the question.
- - In the reasoning, if you need to copy paste some sentences from the context, include them in ##begin_quote## and ##end_quote##. This would mean that things outside of ##begin_quote## and ##end_quote## are not directly copy paste from the context.
- - End your response with final answer in the form <ANSWER>: $answer, the answer should less than 60 words.
- You MUST begin your final answer with the tag "<ANSWER>:". <|eot_id|><|start_header_id|>assistant<|end_header_id|>
- eval_file: "./eval_llama.json"
- model_name: "raft-8b"
- data_dir: "./data"
- rag_topk: 5
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