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.
πββοΈRun
π Examples
π API
Supports ChatML & Jinja
GPT-4 Vision (openai)
GPT-4 Turbo (openai)
GPT-4 (openai)
GPT-4 32K (openai)
ChatGPT (openai)
ChatGPT 16k (openai)
Llama 2 (Meta AI)
PaLM 2 Text (Google)
PaLM 2 Chat (Google)
GPT-3.5 Davinci-3 (openai)
GPT-3.5 Davinci-2 (openai)
Curie (openai)
Babbage (openai)
Ada (openai)
βοΈ Settings
Avoid Repetition
How many answers should the copilot generate? Additional answer outputs increase the cost of each run.
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.
Title
Notes
Run cost = 31 credits
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Input a Google search query + your website & keywords to get AI search engine optimized content. This workflow parses the current top ranked sites and generates the best page summary for your site using OpenAIβs GPT3.
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Create customized chatbots from your own docs/PDF/webpages. Craft your own bot prompts using the creative GPT3, fast GPT 3.5-turbo or powerful GPT4 & optionally prevent hallucinations by constraining all answers to just your citations. Available as Facebook, Instagram, WhatsApp bots or via API. Add multi-lingual speech recognition and text-to-speech in 100+ languages and even video responses. Collect ππΎ ππ½ feedback + see usage & retention graphs too! This is the workflow that powers https://Farmer.CHAT and it's yours to tweak.
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