mirror of
https://github.com/ggerganov/llama.cpp
synced 2026-03-03 13:50:01 +01:00
0becb22ac0
* Try IQ4_NL with blocks of 64 - does not look good * iq4_xs: go to super-blocks of 256 and 6-bit scales for blocks of 32 * iq4_xs: CUDA works - 133.2 t/s * iq4_xs: AVX2 dot product * iq4_xs: ARM_NEON dot product * iq4_nl: Metal implementation As usual, Metal / Apple Silicon don't like my quants. * iq3_xs: minor fix * iq4_xs: shrink by using IQ3_S for attn_k and attn_q * iq4_xs: revert using IQ3_S for attn_k and attn_v PPL vs size is good, but CPU performance suffers: on M2 Max TG-128 drops to 21.7 t/s from 28.8, and on a Ryzen-7950X to 14.5 t/s from 15.8 t/s. On CUDA we have 135 t/s when using IQ3_S vs 133 t/s with pure IQ4_XS. * Fix CI * iq4_xs: Added forgotten check for 256 divisibility --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> |
||
|---|---|---|
| .. | ||
| .gitignore | ||
| CMakeLists.txt | ||
| get-model.cpp | ||
| get-model.h | ||
| test-autorelease.cpp | ||
| test-backend-ops.cpp | ||
| test-c.c | ||
| test-chat-template.cpp | ||
| test-double-float.cpp | ||
| test-grad0.cpp | ||
| test-grammar-parser.cpp | ||
| test-llama-grammar.cpp | ||
| test-model-load-cancel.cpp | ||
| test-opt.cpp | ||
| test-quantize-fns.cpp | ||
| test-quantize-perf.cpp | ||
| test-rope.cpp | ||
| test-sampling.cpp | ||
| test-tokenizer-0-falcon.cpp | ||
| test-tokenizer-0-falcon.py | ||
| test-tokenizer-0-llama.cpp | ||
| test-tokenizer-0-llama.py | ||
| test-tokenizer-1-bpe.cpp | ||
| test-tokenizer-1-llama.cpp | ||