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docs: remove tfs_z option from documentation (#8515)

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docs/modelfile.md
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@ -155,7 +155,6 @@ PARAMETER <parameter> <parametervalue>
| temperature | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8) | float | temperature 0.7 |
| seed | Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0) | int | seed 42 |
| stop | Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate `stop` parameters in a modelfile. | string | stop "AI assistant:" |
| tfs_z | Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1) | float | tfs_z 1 |
| num_predict | Maximum number of tokens to predict when generating text. (Default: -1, infinite generation) | int | num_predict 42 |
| top_k | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40) | int | top_k 40 |
| top_p | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9) | float | top_p 0.9 |

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parser/parser_test.go
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@ -490,7 +490,6 @@ func TestParseFileParameters(t *testing.T) {
"top_k 1": {"top_k", "1"},
"top_p 1.0": {"top_p", "1.0"},
"min_p 0.05": {"min_p", "0.05"},
"tfs_z 1.0": {"tfs_z", "1.0"},
"typical_p 1.0": {"typical_p", "1.0"},
"repeat_last_n 1": {"repeat_last_n", "1"},
"temperature 1.0": {"temperature", "1.0"},