llama : adjust default context size + print warnings

[ggerganov]

fix #8817, #9563 (comment)

By default, the examples will use a context size of 4096, instead of the training context of the model. In a lot of cases, the default training context can be very big - 32k to 128k tokens, which causes enormous KV cache allocation and failures for regular hardware.

Also, add warning logs when the specified context size per sequence does not match the training context.

[ngxson]

Thanks! This should prevent me from burning my swapfile whenever I forget to specify -c

Tested and it shows the log too:

> ./llama-cli -m ../models/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf -cnv -p "You are a helpful assistant"
...
llama_new_context_with_model: n_ctx_per_seq (4096) < n_ctx_train (131072) -- the full capacity of the model will not be utilized
...

[ggerganov]

Is 4096 a good value, or should we go lower?

[ngxson]

According to HF hub statistics, the most used model nowadays is the llama 3 (3.1, 3.2) 8B

With a context size of 4096, the KV takes around 512MB which I think is a very reasonable amount.