Roman Translator App via LLM

few-shots learning can be achieved on LLM via in-context learning.

This example shows how to achieve a data app that translates roman dialect.

The input of the model:

<<<

Translate: {wow}

ammazza

Translate: {wow}

da paura

Translate: {come on}:

daje!

Translate: {feeling tired}:

abbiocco

Translate: {nap}:

'na pennica

Translate: {hell yeah}:

avoja

Translate: {it's hot}:

sto ‘a schiumà

Translate: {let's go}:

damose

Translate: {what's up?}:

>>>

The output:

<<< Che succede? >>>

External resources

• Prompt Engineering - Wikipedia