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When released, PaLM 2 not only surpassed other LLMs in translation abilities between multiple languages but also demonstrated significant improvements over Google Translate (see the Technical Report by Google). This example allows you to easily change out the languages and translation text via variables to explore this and compare with other LLMs. You can also add your own TSV or CSV glossary in the format spec'ed by Google Translate. This example run (or runs like it) can be imported into the Translation Recipe to compare with traditional translation tools!
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Examples
API
PaLM 2 Chat (Google)
Variables let you pass custom parameters to your workflow. Access a variable in your instruction prompt with Jinja, e.g. {{ my_variable }} Learn more.
{{ my_variable }}
glossary
source_language
target_language
text_to_translate
⚙️ Settings
Avoid Repetition
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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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