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A software developer's time is much more precious than wasting time on sub-optimal models. Open Weights models has it's place (in training custom agents and cu

A software developer's time is much more precious than wasting time on sub-optimal models. Open Weights models has it's place (in training custom agents and custom services), but if you are knowledge worker, using a model even 5% less than SOTA is extremely dumb

thot_experiment 2y ago
100% disagree with this take, the flexibility in controlling the prompt leads to QwenCoder2.5-32b outperforming gpt-o1 and claude sonnet 3.5 for nearly everything that I use it for (true for Gemma-27b and llama3.3-70b, though in this context I'm almost always using the former). A specialist model that's specifically prompted to do the correct thing will outperform a SOTA generic model with a one size fits all system prompt. This is why small autocomplete models can very obviously outperform larger models at that specific task. I am speaking 100% from experience and ignoring all benchmarks in forming this view btw, so maybe it's just my specific situation. Also, in general I don't find the difference between SOTA models and local models to be that significant in the real world even when used in the exact same way.
- k__ 2y ago
  Sounds great. Does this run with VSCode and how hard is it to set this up?
  - thot_experiment 2y ago
    yes, the vscode extension is a one click install, so is ollama which is a separate project that provides local inference you'll then have to download a model, which ollama makes very easy. choosing which one will depend on your hardware but the biggest QwenCoder2.5 you can fit is a very solid starting place. it's not ready for your grandma, but it's easy enough that I'd trust a junior dev to be able to get it done
    - k__ 2y ago
      What's the extension name?
      - thot_experiment 2y ago
        Continue, I talk about it at length in the gp post.
        k__ 2y ago
        Ah, thanks. I just read the parent post, lol.
- edm0nd 2y ago
  Are there any small trained models out there that are specifically for python programming that you know of?
- grandma_tea 2y ago
  Do you have any example prompts or suggestions for coming up with them?

thot_experiment 2y ago

100% disagree with this take, the flexibility in controlling the prompt leads to QwenCoder2.5-32b outperforming gpt-o1 and claude sonnet 3.5 for nearly everything that I use it for (true for Gemma-27b and llama3.3-70b, though in this context I'm almost always using the former). A specialist model that's specifically prompted to do the correct thing will outperform a SOTA generic model with a one size fits all system prompt. This is why small autocomplete models can very obviously outperform larger models at that specific task. I am speaking 100% from experience and ignoring all benchmarks in forming this view btw, so maybe it's just my specific situation. Also, in general I don't find the difference between SOTA models and local models to be that significant in the real world even when used in the exact same way.

k__ 2y ago
Sounds great. Does this run with VSCode and how hard is it to set this up?
- thot_experiment 2y ago
  yes, the vscode extension is a one click install, so is ollama which is a separate project that provides local inference you'll then have to download a model, which ollama makes very easy. choosing which one will depend on your hardware but the biggest QwenCoder2.5 you can fit is a very solid starting place. it's not ready for your grandma, but it's easy enough that I'd trust a junior dev to be able to get it done
  - k__ 2y ago
    What's the extension name?
    - thot_experiment 2y ago
      Continue, I talk about it at length in the gp post.
      - k__ 2y ago
        Ah, thanks. I just read the parent post, lol.
edm0nd 2y ago
Are there any small trained models out there that are specifically for python programming that you know of?
grandma_tea 2y ago
Do you have any example prompts or suggestions for coming up with them?