My experience with Alpaca.cpp

• alpaca.cpp

  94 9,878 9.4 C

  Discontinued Locally run an Instruction-Tuned Chat-Style LLM

I've gotten that error with various attempts at using llama.cpp/alpaca.cpp but honestly don't know what it means. If you Google it, there's not much out there (really just this thread and a couple like it that don't provide much of use). I assume it's some sort of internal "checksum" meant to verify that the model file is indeed a valid model or in the correct format. Did you download the model from the link above? If not try that. If so then I really don't know how to fix it unless there's some new format being used.

• alpaca-lora

  107 18,197 3.6 Jupyter Notebook

  Instruct-tune LLaMA on consumer hardware

In theory, something like this could be used to do it, but according to that source, it took about 5 hours on a 4090 to train the 7B variant even with lora. I've also heard it takes about 18 GB of VRAM to train the 7B variant. Assuming everything scales proportionally, that's ~170 GB to fine-tune the 65B variant. Doing that with 8 A100s for instance would cost a little over $30/hour.

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• alpaca_lora_4bit

  41 529 8.6 Python

There's a repo for tuning Loras on the 4-bit models. Readme says it can train 30B on a single 24GB card with Gradient Checkpointing enabled (which does slow things down quite a lot).

• llamacpp-for-kobold

  8 96 10.0 C

  Discontinued Port of Facebook's LLaMA model in C/C++ [Moved to: https://github.com/LostRuins/koboldcpp]

I don't know if anything like that exists. There is this project that I played around with at one point if that helps at all.

• alpaca.cpp

  1 0 6.3

  Locally run an Instruction-Tuned Chat-Style LLM (by trevtravtrev)

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