[Tostino]

So I described my approach to how I fine tune a specific task below to another user, but I'll copy it here:

> Design your tasks to be repeatable and small steps, call the OpenAI API and log all requests/responses. > Filter out any bad responses and take a representative sample of the data you have collected from OpenAI,and train a Mistral or Llama2 model with the request/response pairs.

> Measure the quality of your model vs OpenAI for the same inputs, and then swap out the model in your workflow once happy with the results.

[capableweb]

If you do this, be careful how/if you publish your weights trained on OpenAI output as if they look into how it was generated and it becomes clear you broke the ToS, they'll most likely ban you from the platform.

[leereeves]

How would they "look into how it was generated"?

[capableweb]

You train your model, publish it on huggingface and then write in the README:

> This is how I made this model: Design your tasks to be repeatable and small steps, call the OpenAI API and log all requests/responses. > Filter out any bad responses and take a representative sample of the data you have collected from OpenAI,and train a Mistral or Llama2 model with the request/response pairs.

Just one example.

[Tostino]

I'm not competing with OpenAI in any sense of the word.

[jiveturkey]

I haven't read the ToS, but it may not specifically require competing to be a violation.