Post
2202
๐ก๐ฒ๐ ๐ฆ๐ฝ๐ฎ๐ฐ๐ฒ: ๐ผ๐ ๐๐ง๐๐ซ๐๐ก ๐ฅ๐ก๐๐ฃ๐ฃ๐๐ง ๐บ๏ธ๐๏ธ Plan your next vacation in a few minutes!
I wanted to try out if a powerful LLM like Mixtral-8x7b had geographical reasoning capabilities.
So I built a small space that prompts the LLM to provide a JSON list of places based on a user input.
And the result was impressive! ๐คฏ
โ ๐๐ ๐๐ฒ๐ฒ๐บ๐ ๐น๐ถ๐ธ๐ฒ ๐ ๐ถ๐ ๐๐ฟ๐ฎ๐น ๐ต๐ฎ๐ ๐ฎ ๐ด๐ฟ๐ฎ๐๐ฝ ๐ผ๐ณ ๐ด๐ฒ๐ผ๐ด๐ฟ๐ฎ๐ฝ๐ต๐ถ๐ฐ๐ฎ๐น ๐ฐ๐ผ๐ป๐ฐ๐ฒ๐ฝ๐๐ ๐น๐ถ๐ธ๐ฒ ๐ก๐ผ๐ฟ๐๐ต - ๐ฆ๐ผ๐๐๐ต, ๐ผ๐ฟ ๐๐ฝ๐ฎ๐๐ถ๐ฎ๐น ๐ฎ๐น๐ถ๐ด๐ป๐บ๐ฒ๐ป๐.๐งญ Not just describing these concepts, but really applying them in practice, for instance to successfully answer "give me 4 European cities that are aligned on the map". This is a ๐ป๐ถ๐ฐ๐ฒ ๐ฒ๐ ๐ฎ๐บ๐ฝ๐น๐ฒ ๐ผ๐ณ ๐ฎ๐ป ๐ฒ๐บ๐ฒ๐ฟ๐ด๐ฒ๐ป๐ ๐ฐ๐ฎ๐ฝ๐ฎ๐ฏ๐ถ๐น๐ถ๐๐, since nothing in the LLM's training data should prepare it for this specific task.
Anyway, I added API calls and a nice visualization on top of the LLM, streaming output, caching for the answers and locations... and ta-da! โจ I got the ๐๐ ๐ง๐ฟ๐ฎ๐๐ฒ๐น ๐ฃ๐น๐ฎ๐ป๐ป๐ฒ๐ฟ.
๐๐ค๐ช ๐๐๐ฃ ๐๐๐จ๐๐ง๐๐๐ ๐๐ฉ ๐ฎ๐ค๐ช๐ง ๐ฉ๐ง๐๐ฅ, ๐๐ฃ๐ ๐๐ฉ ๐ฌ๐๐ก๐ก ๐๐ค๐ข๐ ๐ช๐ฅ ๐ฌ๐๐ฉ๐ ๐ฃ๐๐๐ ๐๐ฃ๐ ๐๐ค๐ฃ๐ซ๐๐ฃ๐๐๐ฃ๐ฉ ๐ก๐ค๐๐๐ฉ๐๐ค๐ฃ๐จ!
๐๐ง๐ฎ ๐๐ฉ ๐๐๐ง๐ ๐ m-ric/ai-travel-planner
Thank you @freddyaboulton for the ๐๐๐๐๐๐_๐๐๐๐๐๐ component, and @clem , @pngwn , @abidlabs for your ideas and support!
I wanted to try out if a powerful LLM like Mixtral-8x7b had geographical reasoning capabilities.
So I built a small space that prompts the LLM to provide a JSON list of places based on a user input.
And the result was impressive! ๐คฏ
โ ๐๐ ๐๐ฒ๐ฒ๐บ๐ ๐น๐ถ๐ธ๐ฒ ๐ ๐ถ๐ ๐๐ฟ๐ฎ๐น ๐ต๐ฎ๐ ๐ฎ ๐ด๐ฟ๐ฎ๐๐ฝ ๐ผ๐ณ ๐ด๐ฒ๐ผ๐ด๐ฟ๐ฎ๐ฝ๐ต๐ถ๐ฐ๐ฎ๐น ๐ฐ๐ผ๐ป๐ฐ๐ฒ๐ฝ๐๐ ๐น๐ถ๐ธ๐ฒ ๐ก๐ผ๐ฟ๐๐ต - ๐ฆ๐ผ๐๐๐ต, ๐ผ๐ฟ ๐๐ฝ๐ฎ๐๐ถ๐ฎ๐น ๐ฎ๐น๐ถ๐ด๐ป๐บ๐ฒ๐ป๐.๐งญ Not just describing these concepts, but really applying them in practice, for instance to successfully answer "give me 4 European cities that are aligned on the map". This is a ๐ป๐ถ๐ฐ๐ฒ ๐ฒ๐ ๐ฎ๐บ๐ฝ๐น๐ฒ ๐ผ๐ณ ๐ฎ๐ป ๐ฒ๐บ๐ฒ๐ฟ๐ด๐ฒ๐ป๐ ๐ฐ๐ฎ๐ฝ๐ฎ๐ฏ๐ถ๐น๐ถ๐๐, since nothing in the LLM's training data should prepare it for this specific task.
Anyway, I added API calls and a nice visualization on top of the LLM, streaming output, caching for the answers and locations... and ta-da! โจ I got the ๐๐ ๐ง๐ฟ๐ฎ๐๐ฒ๐น ๐ฃ๐น๐ฎ๐ป๐ป๐ฒ๐ฟ.
๐๐ค๐ช ๐๐๐ฃ ๐๐๐จ๐๐ง๐๐๐ ๐๐ฉ ๐ฎ๐ค๐ช๐ง ๐ฉ๐ง๐๐ฅ, ๐๐ฃ๐ ๐๐ฉ ๐ฌ๐๐ก๐ก ๐๐ค๐ข๐ ๐ช๐ฅ ๐ฌ๐๐ฉ๐ ๐ฃ๐๐๐ ๐๐ฃ๐ ๐๐ค๐ฃ๐ซ๐๐ฃ๐๐๐ฃ๐ฉ ๐ก๐ค๐๐๐ฉ๐๐ค๐ฃ๐จ!
๐๐ง๐ฎ ๐๐ฉ ๐๐๐ง๐ ๐ m-ric/ai-travel-planner
Thank you @freddyaboulton for the ๐๐๐๐๐๐_๐๐๐๐๐๐ component, and @clem , @pngwn , @abidlabs for your ideas and support!
