LLMs have biases built into them that are subtly reflected in every reference they produce about a subject. These biases will shortly be embedded to every Word Doc, Powerpoint, text and gmail message they help us create. Below we explore what 4 different versions of GPT feel about a collection of car brands.
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The maximum number of tokens to generate in the completion. Increase to generate longer responses.
Higher values allow the LLM to take more risks. Try values larger than 1 for more creative applications or 0 to ensure that LLM gives the same answer when given the same user input.
How many answers should the copilot generate? Additional answer outputs increase the cost of each run.
Run cost = 1 credits
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PaLM 2 Text (Google)
Llama 2 70b Chat [Deprecated] (Meta AI)
ChatGPT (openai)
GPT-4 (openai)
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