Hi, I have searched for a long time on this subreddit, in Ooba’s documentation, Mistral’s documentation and everything, but I just can’t find what I am looking for.
I see everyone claiming Mistral can handle up to 32k context size, however while it technically won’t refuse to generate anything above like 8k, the output is just not good. I have it loaded in Oobabooga’s text-generation-webui and am using the API through SillyTavern. I loaded the normal Mistral 7B just to check, but with my current 12k story, all it can generate is gibberish if I give it the full context. However, I also checked using other fine-tunes of Mistral.
What am I doing wrong? I am using the GPTQ version on my RX 7900 XTX. Is it just advertising that it won’t crash until 32k or something, or am I doing something wrong for not getting coherent output above 8k? I did mess with the alpha values, and while doing so does eliminate the gibberish, I do get the idea that the quality does suffer somehow.
I noticed this problem in llama.cpp too. I suspect that it may be because something is not implemented, that is required for Mistral models, e.g. sliding window attention. To confirm that, one can compare outputs from PyTorch with other software. I tried to do it, but PyTorch model runs out of system RAM with ~15k token prompt.