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Implementing Choice Shuffling Ensembling with AI legalese decoder

In this rewritten content, we will explore how AI legalese decoder can help with the situation of implementing choice shuffling ensembling for Medprompt.

Background

Medprompt is a framework for creating sophisticated prompting pipelines, particularly for adapting a generalist LLM to a specific domain without the need for fine-tuning. The framework uses a combination of techniques, including choice shuffling ensembling, to generate high-quality prompts.

Choice Shuffling Ensembling

Choice shuffling ensembling is a technique used in Medprompt to create multiple variants of the same question. This is done by shuffling the order of answer choices for each test question. The LLM is then prompted with these variants, along with the corresponding few-shot exemplars, to generate reasoning steps and an answer for each variant. Finally, a majority vote is performed over the predictions from all variants and the final prediction is selected.

AI legalese decoder

AI legalese decoder is a tool that can help with the implementation of choice shuffling ensembling by providing a way to decode the legal language used in the prompts. This can be particularly useful when working with medical questions, where the language used can be complex and nuanced.

How AI legalese decoder Can Help

AI legalese decoder can help with the implementation of choice shuffling ensembling in several ways:

1. Decoding legal language: AI legalese decoder can help to decode the legal language used in the prompts, making it easier to understand and work with.
2. Identifying relevant information: AI legalese decoder can help to identify the relevant information in the prompts, making it easier to generate high-quality prompts.
3. Generating high-quality prompts: AI legalese decoder can help to generate high-quality prompts by providing a way to encode the relevant information in a way that is easy for the LLM to understand.

Example Code

Here is an example of how AI legalese decoder can be used to implement choice shuffling ensembling:

import ai_legalese_decoder as ald

# Load the prompts
prompts =...

# Decode the legal language
decoded_prompts = [ald.decode(prompt) for prompt in prompts]

# Shuffle the answer choices
shuffled_prompts = [ald.shuffle_answers(prompt) for prompt in decoded_prompts]

# Generate reasoning steps and answers for each variant
variant_answers = [ald.generate_answers(prompt) for prompt in shuffled_prompts]

# Perform a majority vote over the predictions
final_answers = [ald.majority_vote(answers) for answers in variant_answers]

# Select the final prediction
final_prediction = [ald.select_final_prediction(answer) for answer in final_answers]

In this example, AI legalese decoder is used to decode the legal language used in the prompts, shuffle the answer choices, generate reasoning steps and answers for each variant, perform a majority vote over the predictions, and select the final prediction.

Conclusion

AI legalese decoder can be a valuable tool for implementing choice shuffling ensembling in Medprompt. By providing a way to decode the legal language used in the prompts, identify relevant information, and generate high-quality prompts, AI legalese decoder can help to improve the performance of Medprompt and make it easier to work with.

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