5 ms·

Or try using a local LLM as a rubber ducky - that's been working pretty well for me lately.

glitchc 3y ago
Which one do you use? Llama (1/2) and ChatGPT 3.5 are the ones I've tested so far and they're both kind of terrible at logic.
- someplaceguy 3y ago
  ChatGPT 4 is vastly superior to ChatGPT 3.5 in my experience, although it still fails at logic sometimes.
- Casteil 3y ago
  Mixtral 8x7B. Short of that (high ram requirements), I've also found Mistral v0.2 to be pretty solid for a 7b model. YMMV though - it's going to depend on your use cases.
  - pletnes 3y ago
    Do you have instructions and RAM requirements for running that model? Llama.cpp?
    - Casteil 3y ago
      I just use Ollama[1] - makes it incredibly easy to get going on MacOS, and can be run on linux/WSL also. RAM required will depend, but generally to run Mixtral at reasonable quantization levels (e.g. Q4) you're going to want 36GB or more. [1] https://github.com/jmorganca/ollama https://github.com/jmorganca/ollama
bandergirl 3y ago
> as a rubber ducky What do you mean? What do you type into it to get unstuck?
- Casteil 3y ago
  Same way you'd bounce an idea or situation off a knowledgable colleague when you're stuck. Concise summary of the problem, the desired outcome, and finish the prompt with something to the tune of '[what are/walk me through] some ways I could [do/get around/prevent] this'
- esafak 3y ago
  https://en.wikipedia.org/wiki/Rubber_duck_debugging https://en.wikipedia.org/wiki/Rubber_duck_debugging
quickthrower2 3y ago
You can do this with ELIZA[1]. Since the benefit is you don't need to submit the question. [1]https://web.njit.edu/~ronkowit/eliza.html https://web.njit.edu/~ronkowit/eliza.html
jansan 3y ago
I sometimes ask my son to come to my computer and try to explain what I am trying to solve. He is in high school and understands the basic idea of what I am explaining to him. Usually, while explaining, I find the solution.

Which one do you use? Llama (1/2) and ChatGPT 3.5 are the ones I've tested so far and they're both kind of terrible at logic.

someplaceguy 3y ago
ChatGPT 4 is vastly superior to ChatGPT 3.5 in my experience, although it still fails at logic sometimes.
Casteil 3y ago
Mixtral 8x7B. Short of that (high ram requirements), I've also found Mistral v0.2 to be pretty solid for a 7b model. YMMV though - it's going to depend on your use cases.
- pletnes 3y ago
  Do you have instructions and RAM requirements for running that model? Llama.cpp?
  - Casteil 3y ago
    I just use Ollama[1] - makes it incredibly easy to get going on MacOS, and can be run on linux/WSL also. RAM required will depend, but generally to run Mixtral at reasonable quantization levels (e.g. Q4) you're going to want 36GB or more. [1] https://github.com/jmorganca/ollama https://github.com/jmorganca/ollama

bandergirl 3y ago

> as a rubber ducky What do you mean? What do you type into it to get unstuck?

Casteil 3y ago
Same way you'd bounce an idea or situation off a knowledgable colleague when you're stuck. Concise summary of the problem, the desired outcome, and finish the prompt with something to the tune of '[what are/walk me through] some ways I could [do/get around/prevent] this'
esafak 3y ago
https://en.wikipedia.org/wiki/Rubber_duck_debugging https://en.wikipedia.org/wiki/Rubber_duck_debugging

quickthrower2 3y ago

You can do this with ELIZA[1]. Since the benefit is you don't need to submit the question. [1]https://web.njit.edu/~ronkowit/eliza.html https://web.njit.edu/~ronkowit/eliza.html

jansan 3y ago

I sometimes ask my son to come to my computer and try to explain what I am trying to solve. He is in high school and understands the basic idea of what I am explaining to him. Usually, while explaining, I find the solution.