Great tutorial! I’m interested in learning more about how to iterate between the testing and training until you get to a sufficient quality of inference.
🐴 Fascinating! I have an OpenAI API-utilizing, localized web platform that uses the OpenAI API function calls to query/fetch extra data and such, I have been thinking if I should try out fine-tuning a GPT-3.5-16k instance for specific use case scenarios such as customer service bots that are up-to-date and would need less extra data fetching. This is especially important in non-English primary use cases where I find GPT-3.5's wording a bit lacking at times. Will definitely have to take a look at it. Thanks for the video. Regards, Horse
![[UNCUT] “บอสณวัฒน์” ลากไส้!! ใครหนุนหลัง "แม่ตั๊ก ป๋าเบียร์" I คนดังนั่งเคลียร์ I 30 ก.ย. 67](http://i.ytimg.com/vi/QlD7mU2KKRk/mqdefault.jpg)
Awesome, simple and easy to understand..
Awesome explanation! Thanks!
Great tutorial! I’m interested in learning more about how to iterate between the testing and training until you get to a sufficient quality of inference.
Thanks! Easy to understand
🐴 Fascinating! I have an OpenAI API-utilizing, localized web platform that uses the OpenAI API function calls to query/fetch extra data and such, I have been thinking if I should try out fine-tuning a GPT-3.5-16k instance for specific use case scenarios such as customer service bots that are up-to-date and would need less extra data fetching. This is especially important in non-English primary use cases where I find GPT-3.5's wording a bit lacking at times. Will definitely have to take a look at it. Thanks for the video. Regards, Horse