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examples/summarize_scoring_using_bedrock.ipynb

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"\n",
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"# Make sure you've set the BENCH_FILE_DIR environment variable\n",
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"\n",
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"# The summary_quality scorer uses ChatGPT to score the summary\n",
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"# The summary_quality scorer uses gpt-3.5-turbo to score the summary\n",
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"# so make sure that your OPENAI_API_KEY environment variable is set\n",
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"\n",
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"combos = list(combinations(models, 2))\n",
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 16,
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"id": "1f1185e4-b39d-4107-bbc4-3aedc449cf46",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[('anthropic.claude-v2', 1345.4153155340496), ('meta.llama2-70b-chat-v1', 1079.6979024278733), ('amazon.titan-text-lite-v1', 898.4211374051577), ('anthropic.claude-v1', 864.5103513782595), ('meta.llama2-13b-chat-v1', 811.9552932546615)]\n"
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"Model anthropic.claude-v2: Rating 1345.4153155340496\n",
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"Model meta.llama2-70b-chat-v1: Rating 1079.6979024278733\n",
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"Model amazon.titan-text-lite-v1: Rating 898.4211374051577\n",
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"Model anthropic.claude-v1: Rating 864.5103513782595\n",
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"Model meta.llama2-13b-chat-v1: Rating 811.9552932546615\n"
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]
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}
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],

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