rellm VS llama.cpp

- https://github.com/r2d4/rellm

MS guidance as mentioned and ReLLM

There's probably a better API that wraps generate, but there's a bit more work than the logit mask.

You have to go one token at a time, otherwise the masking becomes combinatoric rather than linear (two tokens at a time -- need to generate all two token pairs, etc.).

But otherwise, that's what the code does! https://github.com/r2d4/rellm/blob/main/rellm/rellm.py#L21

if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp

the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...

And you can search for any GGUF on huggingface

Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182

For anyone interested in exploring this, llama.cpp has an example implementation here:

https://github.com/ggerganov/llama.cpp/tree/master/examples/...

Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.

well https://github.com/ggerganov/llama.cpp/issues/6849