gpt-3 VS dalle-mini

Are generative AI models useful for learning a language, and if so which languages? Over 90% of ChatGPT's training data was in English. The remaining 10% of data was split unevenly between 100+ languages. This suggests that the quality of the outputs will vary from language to language.

I have doubts it was extensively trained on German data. Who knows about GPT4, but GPT3 is ~92% of English and ~1.5% of German, which means it saw more "die, motherfucker, die" than on "die Mutter".

(https://github.com/openai/gpt-3/blob/master/dataset_statisti...)

Catalan was 0.018 % of GPT-3's training corpus. https://github.com/openai/gpt-3/blob/master/dataset_statistics/languages_by_word_count.csv.

>Certainly it is pleasing that they are not just doing Hindi, but some of these languages must be represented online by a very small corpus of text indeed. I wonder how effectively an LLM can be trained on such a small training set for any given language?

as long as it's not the main language it doesn't really matter. Besides English(92.6%), the biggest language by representation (word count) is taken up by french at 1.8%. Most of the languages GPT-3 knows are sitting at <0.2% representation.

https://github.com/openai/gpt-3/blob/master/dataset_statisti...

Competence in the main language will bleed into the rest.

And from skimming their GH page, it seems it'd be costly to host as well

Mini-Gemini is a bit of a confusing name.

Reminds me of how DALL·E Mini came out three years ago and eventually had to rename itself to Craiyon https://github.com/borisdayma/dalle-mini

I wouldnt consider Craiyon to be high tier equipment

Made with : https://www.craiyon.com/

AI Site

https://www.craiyon.com/ try it, and it's not even that good a text to image generator.

For example used just your prompt on Craiyon , guess you can try on replicate the free sd demos for example.