Can you help me understand, how the examples being chosen out of trainset provided in Botstrapfewshot. Also, I understand that it add rationale in the questions but like how Bootstrapfewshot works. Can you go in the code and try to gather the information, the teacher and student model, it was not clear.
@@AmanIndia-m5l github.com/stanfordnlp/dspy/blob/main/dspy%2Fteleprompt%2Fbootstrap.py The above script implements the bootstrapwitheandomsearch and there is random_search in the same path which implements the BsFsWRs algo. To understand the working, you have to get comfortable with how metrics works, and how bootstrap withfewshots works..try that first.
This was the best tutorial on DSPy optimisers. You should definitely do one on Asserts and Suggest.
Thank you sir it is an excellent playlist
Very nice content. Thanks!
My dude, you are the GOAT. You're our primary source of DSPy knowledge on new releases. Are you working on a synthesiser video?
Thanks! It would be really helpful if the print output cells colours are better visible.
Found very helpful. Thanks alott for posting.
Can you help me understand, how the examples being chosen out of trainset provided in Botstrapfewshot. Also, I understand that it add rationale in the questions but like how Bootstrapfewshot works.
Can you go in the code and try to gather the information, the teacher and student model, it was not clear.
@@AmanIndia-m5l github.com/stanfordnlp/dspy/blob/main/dspy%2Fteleprompt%2Fbootstrap.py
The above script implements the bootstrapwitheandomsearch and there is random_search in the same path which implements the BsFsWRs algo.
To understand the working, you have to get comfortable with how metrics works, and how bootstrap withfewshots works..try that first.