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authorBarfingLemurs <128182951+BarfingLemurs@users.noreply.github.com>2023-09-27 11:30:36 -0400
committerGitHub <noreply@github.com>2023-09-27 18:30:36 +0300
commitffe88a36a913e5792aa383f0726bdbcf632e7191 (patch)
tree1674d754253bb233833f20245719e48c5b6c74c4 /README.md
parent99115f3fa654b593099c6719ad30e3f54ce231e1 (diff)
readme : add some recent perplexity and bpw measurements to READMES, link for k-quants (#3340)
* Update README.md * Update README.md * Update README.md with k-quants bpw measurements
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@@ -597,6 +597,11 @@ Several quantization methods are supported. They differ in the resulting model d
| 13B | ms/tok @ 8th | - | 73 | 82 | 98 | 105 | 128 |
| 13B | bits/weight | 16.0 | 4.5 | 5.0 | 5.5 | 6.0 | 8.5 |
+- [k-quants](https://github.com/ggerganov/llama.cpp/pull/1684)
+- recent k-quants improvements
+ - [#2707](https://github.com/ggerganov/llama.cpp/pull/2707)
+ - [#2807](https://github.com/ggerganov/llama.cpp/pull/2807)
+
### Perplexity (measuring model quality)
You can use the `perplexity` example to measure perplexity over a given prompt (lower perplexity is better).