Update README.md

README.md

@@ -87,7 +87,7 @@ The process to generate these models is roughly as follows:
 | [DeepSeek-R1-Distill-Llama-8B-F16](./DeepSeek-R1-Distill-Llama-8B-F16.gguf)       | 14.009216 ±0.118474 |   100% |                N/A |           N/A |
 
 ### ARC, HellaSwag, MMLU, Truthful QA and WinoGrande scores
-Scores generated using [llama-perplexity](<https://github.com/ggml-org/llama.cpp/tree/master/examples/perplexity>) with 750 tasks per test, and a context size of 768 tokens. Naive (`llama-quantize` with no optimization) Q4_K_M quantization included for comparison.
+Scores generated using [llama-perplexity](<https://github.com/ggml-org/llama.cpp/tree/master/examples/perplexity>) with 750 tasks per test, and a context size of 768 tokens.
 
 For the test data used in the generation of these scores, follow the appropiate links: [HellaSwag](<https://github.com/klosax/hellaswag_text_data>), [ARC, MMLU, Truthful QA](<https://huggingface.co/datasets/ikawrakow/validation-datasets-for-llama.cpp/tree/main>) and [WinoGrande](<https://huggingface.co/datasets/ikawrakow/winogrande-eval-for-llama.cpp/tree/main>)