Chat gpt works using a combination of rl and llm

Hopefully it is easier to use than pytorch geometric

Maybe say if we can download our answer then in the file we get the answer some watermark is encoded.

You can pre train and finetune energy efficient language models such as electra or convbert in this gpu. But maybe the batch size might not be too big so the descent would be a bit noisy and also keep the corpus size as small as possible.

Look into bio electra paper which also has the notebook on how he has trained it .

True but practically training a gpt model is not computationally cheap. I think instead of making such generalized language models we need to focus more one subject specific language models.

https://github.com/lucidrains/PaLM-rlhf-pytorch

Similar to chat get architecture you can play with this

Do you have target labels for how much defect do you have against the flow?

I believe lack of privacy preserving models/ systems in machine learning is also a cause for concern. In many applications we collect user data (the biggest companies in the world do that) if we are able to train models in a more secure manner(not just federated learning) people might be more inclined to give more info if they can control and we can guarantee no party apart from the user will get a peek at the raw data.

This is my two cents on the topic.