DeepSeek-v3.1

./llama.cpp/llama-cli -hf unsloth/DeepSeek-V3.1-GGUF:UD-Q2_K_XL -ngl 99 --jinja -ot ".ffn_.*_exps.=CPU"

More details on running + optimal params here: https://docs.unsloth.ai/basics/deepseek-v3.1

There is a way to convert to Q8_0, BF16, F16 without compiling llama.cpp, and it's enabled if you use `FastModel` and not on `FastLanguageModel`

Essentially I try to do `sudo apt-get` if it fails then `apt-get` and if all fails, it just fails. We need `build-essential cmake curl libcurl4-openssl-dev`

See https://github.com/unslothai/unsloth-zoo/blob/main/unsloth_z...

You just fail and print a nice error message telling the user exactly what they need to do, including the exact apt command or whatever that they need to run.

I was thinking if I can do it during the pip install or via setup.py which will do the apt-get instead.

As a fallback, I'll probably for now remove shell executions and just warn the user

Some people may prefer using whatever llama.cpp in $PATH, it's okay to support that, though I'd say doing so may lead to more confused noob users spam - they may just have an outdated version lurking in $PATH.

Doing so makes unsloth wheel platform-dependent, if this is too much of a burden, then maybe you can just package llama.cpp binary and have it on PyPI, like how scipy guys maintain a https://pypi.org/project/cmake/ on PyPI (yes, you can `pip install cmake`), and then depends on it (maybe in an optional group, I see you already have a lot due to cuda shit).

I'm still working on it, but sadly I'm not a packaging person so progress has been nearly zero :(