Aiedail

This is commendable, but there's room for improvement. Up until now, SOTA-level "open-source" LLM models (LLaMA, Mistral, etc.) have usually only made their inference code and model architecture public. While these elements are not insignificant, they are somewhat trivial when compared to the training code and training datasets, as these two factors largely determine the performance of the model. This is not open at all. It goes without saying that sharing the training datasets and process with other AI researchers is crucial. This transparency would not only help to improve the model(for others could contribute to it) but also contribute to the whole community, as they usually advertised. Otherwise, it will be difficult for these efforts to truly promote the development of LLM.

Is there a similar tool for python? I don't like the DAP solution but prefer a gdb like python debugger :(

Have you ever tried a bright environment and dark mode monitor? I'm working with this one about 3 years and it makes me both relax and comfortable.

I'm curious about what makes this project special, see there's a lot of similar implementations of diffusion models based on pytorch/tf. Is it because it use the cpu itself to produce the diffusion process?