@@ -50,7 +50,7 @@ function extremeTopK(testCase)
5050 %% This should work, and it does on some computers. On others, Ollama
5151 %% receives the parameter, but either Ollama or llama.cpp fails to
5252 %% honor it correctly.
53- % testCase.assumeTrue(false,"disabled due to Ollama/llama.cpp not honoring parameter reliably");
53+ testCase .assumeTrue(false ," disabled due to Ollama/llama.cpp not honoring parameter reliably" );
5454
5555 % setting top-k to k=1 leaves no random choice,
5656 % so we expect to get a fixed response.
@@ -65,7 +65,7 @@ function extremeMinP(testCase)
6565 %% This should work, and it does on some computers. On others, Ollama
6666 %% receives the parameter, but either Ollama or llama.cpp fails to
6767 %% honor it correctly.
68- % testCase.assumeTrue(false,"disabled due to Ollama/llama.cpp not honoring parameter reliably");
68+ testCase .assumeTrue(false ," disabled due to Ollama/llama.cpp not honoring parameter reliably" );
6969
7070 % setting min-p to p=1 means only tokens with the same logit as
7171 % the most likely one can be chosen, which will almost certainly
@@ -81,7 +81,7 @@ function extremeTfsZ(testCase)
8181 %% This should work, and it does on some computers. On others, Ollama
8282 %% receives the parameter, but either Ollama or llama.cpp fails to
8383 %% honor it correctly.
84- % testCase.assumeTrue(false,"disabled due to Ollama/llama.cpp not honoring parameter reliably");
84+ testCase .assumeTrue(false ," disabled due to Ollama/llama.cpp not honoring parameter reliably" );
8585
8686 % setting tfs_z to z=0 leaves no random choice, but degrades to
8787 % greedy sampling, so we expect to get a fixed response.
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