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Alpaca-Llama-3-8B

Some GGUF quantizations can be found in https://huggingface.co/akumaburn/Alpaca-Llama-3-8B-GGUF

mistral-7b-openorca.Q8_0.gguf:

  • MMLU-Test: Final result: 41.5836 +/- 0.4174
  • Arc-Easy: Final result: 72.6316 +/- 1.8691
  • Truthful QA: Final result: 32.0685 +/- 1.6339
  • Arc-Challenge: Final result: 48.8294 +/- 2.8956

llama-3-8b-bnb-4bit.Q8_0.gguf:

  • MMLU-Test: Final result: 40.4074 +/- 0.4156
  • Arc-Easy: Final result: 73.8596 +/- 1.8421
  • Truthful QA: Final result: 26.6830 +/- 1.5484
  • Arc-Challenge: Final result: 46.8227 +/- 2.8906

Open_Orca_Llama-3-8B-unsloth.Q8_0.gguf:

  • MMLU-Test: Final result: 39.3818 +/- 0.4138
  • Arc-Easy: Final result: 67.3684 +/- 1.9656
  • Truthful QA: Final result: 29.0086 +/- 1.5886
  • Arc-Challenge: Final result: 42.1405 +/- 2.8604

Alpaca-Llama-3-8B-GGUF-unsloth.Q8_0.gguf:

  • MMLU-Test: Final result: 40.6441 +/- 0.4160
  • Arc-Easy: Final result: 77.5439 +/- 1.7494
  • Truthful QA: Final result: 29.7430 +/- 1.6003
  • Arc-Challenge: Final result: 50.5017 +/- 2.8963

Meta-Llama-3-8B.Q8_0.gguf:

  • MMLU-Test: Final result: 40.8664 +/- 0.4163
  • Arc-Easy: Final result: 74.3860 +/- 1.8299
  • Truthful QA: Final result: 28.6414 +/- 1.5826
  • Arc-Challenge: Final result: 47.1572 +/- 2.8917

Llama.cpp Options For Testing: --samplers "tfs;typical;temp" --draft 32 --ctx-size 8192 --temp 0.82 --tfs 0.8 --typical 1.1 --repeat-last-n 512 --batch-size 8192 --repeat-penalty 1.0 --n-gpu-layers 100 --threads 12

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

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