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| author | Kawrakow <48489457+ikawrakow@users.noreply.github.com> | 2024-07-28 12:11:59 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2024-07-28 12:11:59 +0200 |
| commit | 291066e6df5318c322a03e592483aae8820d3b19 (patch) | |
| tree | 1c8cafa8d0bc73c3aa39c71ab53b53eb307d3774 /examples/quantize/quantize.cpp | |
| parent | f62615b44f7df586cb58ed9fffca59b96820117b (diff) | |
IQ4_K: SOTA 4-bit quantization (#6)
* iq4_k: basics
* quantize/dequantize works
* CUDA dequantize works and one can run PPL calcs. I get
PPL = 6.5258 for LlaMA-3.1-8B, which is 1.77% above fp16.
In comparison, q4_K_S (same size) is 2.88% above fp16.
* TG on CUDA does not work. Johannes has changed the way i-quant dot
products are done, so need to sort out what he had in mind
* iqk_mul_mat is not implemented.
* iq4_k: TG now works on CUDA
* iq4_k: AVX512 implementation
For LLaMA-3.1-8B we get PP-512 = 182.6 t/s, TG-128 = 13.6 t/s,
so almost the same as q4_K_S.
* iq4_k: AVX2 implementation
For LLaMA-3.1-8B we get PP-512 = 203.1 t/s, TG-128 = 12.9 t/s
on the Ryzen-5975X.
* iq4_k: NEON implementation
For LLaMA-3.1-8B we get PP-512 = 60.7 t/s, TG-128 = 25.0 t/s
on the M2-Max. TG is on par with q4_K_S, PP is ~10% slower.
* iq4_k: Metal implementation
For LLaMA-3.1-8B we get PP-512 = 445 t/s, TG-128 = 46.3 t/s
on a 30-core M2-Max GPU. This is to be compared with (currently)
PP-512 = 460 t/s, TG-128 = 51 t/s for q4_K_S.
* iq4_k: scalar dot product
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Diffstat (limited to 'examples/quantize/quantize.cpp')
| -rw-r--r-- | examples/quantize/quantize.cpp | 1 |
1 files changed, 1 insertions, 0 deletions
diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 059d67a6..2397e202 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -40,6 +40,7 @@ static const std::vector<struct quant_option> QUANT_OPTIONS = { { "Q3_K_L", LLAMA_FTYPE_MOSTLY_Q3_K_L, " 3.35G, +0.1764 ppl @ LLaMA-v1-7B", }, { "IQ4_NL", LLAMA_FTYPE_MOSTLY_IQ4_NL, " 4.50 bpw non-linear quantization", }, { "IQ4_XS", LLAMA_FTYPE_MOSTLY_IQ4_XS, " 4.25 bpw non-linear quantization", }, + { "IQ4_K", LLAMA_FTYPE_MOSTLY_IQ4_K, " 4.5 bpw non-linear quantization", }, { "Q4_K", LLAMA_FTYPE_MOSTLY_Q4_K_M, "alias for Q4_K_M", }, { "Q4_K_S", LLAMA_FTYPE_MOSTLY_Q4_K_S, " 3.59G, +0.0992 ppl @ LLaMA-v1-7B", }, { "Q4_K_M", LLAMA_FTYPE_MOSTLY_Q4_K_M, " 3.80G, +0.0532 ppl @ LLaMA-v1-7B", }, |