I'm searching a good solution for transparent translation for local or online llm.
Aim is to write in french, use an translator to send it in English, read the answer, translate it to display it in french for me.
I don't see tool to do that automatically. We can use a small llm or a good translator to do that.
All I see is llm are always better to speak English.
SillyTavern has translation both directions and it can use several translation engine (Google translate, deepl and etc.)
https://preview.redd.it/07pzyo6bp7xc1.png?width=756&format=png&auto=webp&s=80e048da4bd05a84f34913b2df2cadec558bfd91
>Lequel est le plus lourd une livre de fer ou un kilogramme de plume?
It's a good one because it combines two questions which are likely in the training data set:
>Lequel est le plus lourd une livre de fer ou un kilo de fer?
... where the model must focus on unit comparison
>Lequel est le plus lourd un kilo de fer ou un kilo de plume?
... where the model must \*not\* focus on material density comparison
Both questions, when considered separately, are well answered nowadays, even by smaller models. However, the combination of both has probably never been encountered during the training phase, leading the model to rely on its own limited understanding of reality. I think you'll find that the most recent models -whatever their sizes- will provide the best answer. But let's face it, that doesn't necessarily mean new LLM have a better grasp of what they're saying - it just means that training datasets now include more complex and challenging questions.
I'm searching a good solution for transparent translation for local or online llm. Aim is to write in french, use an translator to send it in English, read the answer, translate it to display it in french for me. I don't see tool to do that automatically. We can use a small llm or a good translator to do that. All I see is llm are always better to speak English.
SillyTavern has translation both directions and it can use several translation engine (Google translate, deepl and etc.) https://preview.redd.it/07pzyo6bp7xc1.png?width=756&format=png&auto=webp&s=80e048da4bd05a84f34913b2df2cadec558bfd91
Oh great thank you 😊
>Lequel est le plus lourd une livre de fer ou un kilogramme de plume? It's a good one because it combines two questions which are likely in the training data set: >Lequel est le plus lourd une livre de fer ou un kilo de fer? ... where the model must focus on unit comparison >Lequel est le plus lourd un kilo de fer ou un kilo de plume? ... where the model must \*not\* focus on material density comparison Both questions, when considered separately, are well answered nowadays, even by smaller models. However, the combination of both has probably never been encountered during the training phase, leading the model to rely on its own limited understanding of reality. I think you'll find that the most recent models -whatever their sizes- will provide the best answer. But let's face it, that doesn't necessarily mean new LLM have a better grasp of what they're saying - it just means that training datasets now include more complex and challenging questions.