Lumpiasty/llama.cpp
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sampler : remove "full-context windows" from history-based samplers (#26524)

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* Resolve -1 to 1024 instead of ctx-len for samplers

Because of backend-sampling we initialize samplers before the complete
llama_context is there. Therefore, we cannot infer the resolved context
length yet at the time we construct the samplers.

* Shared default of 64 for history-based samplers, remove context_size
This commit is contained in:
Oliver Simons
2026-08-04 21:28:55 +03:00
committed by GitHub
parent 76c956c137
commit a6aa6f5450
18 changed files with 52 additions and 80 deletions
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tools/server/server-schema.cpp
+4 -14
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@@ -124,8 +124,8 @@ std::vector<std::unique_ptr<field>> make_llama_cmpl_schema(const common_params &
->set_desc("Dynamic temperature exponent, controls how entropy maps to temperature"));
add((new field_num("repeat_last_n", params.sampling.penalty_last_n))
->set_hard_limits(-1, INT32_MAX)
->set_desc("Last n tokens to consider for penalizing repetition (0 = disabled, -1 = ctx-size)"));
->set_hard_limits(0, INT32_MAX)
->set_desc("Last n tokens to consider for penalizing repetition (0 = disabled)"));
add((new field_num("repeat_penalty", params.sampling.penalty_repeat))
->set_desc("Control the repetition of token sequences in the generated text (1.0 = disabled)"));
@@ -151,8 +151,8 @@ std::vector<std::unique_ptr<field>> make_llama_cmpl_schema(const common_params &
->set_desc("Tokens that extend repetition beyond this length receive exponentially increasing penalty: multiplier * base ^ (sequence_length - allowed_length)"));
add((new field_num("dry_penalty_last_n", params.sampling.dry_penalty_last_n))
->set_hard_limits(-1, INT32_MAX)
->set_desc("How many tokens to scan for repetitions (0 = disabled, -1 = context size)"));
->set_hard_limits(0, INT32_MAX)
->set_desc("How many tokens to scan for repetitions (0 = disabled)"));
add((new field_num("mirostat", params.sampling.mirostat))
->set_limits(0, 2)
@@ -515,7 +515,6 @@ std::vector<std::unique_ptr<field>> make_llama_cmpl_schema(const common_params &
task_params eval_llama_cmpl_schema(
const llama_vocab * vocab,
const common_params & params_base,
const int n_ctx_slot,
const std::vector<llama_logit_bias> & logit_bias_eog,
const json & data) {
task_params params;
@@ -549,15 +548,6 @@ task_params eval_llama_cmpl_schema(
// post-processing
{
if (params.sampling.penalty_last_n == -1) {
// note: should be the slot's context and not the full context, but it's ok
params.sampling.penalty_last_n = n_ctx_slot;
}
if (params.sampling.dry_penalty_last_n == -1) {
params.sampling.dry_penalty_last_n = n_ctx_slot;
}
// if "reasoning_format" is not provided, its handler will not be called, we will need to handle it here
auto reasoning_format = params.chat_parser_params.reasoning_format;
params.chat_parser_params.reasoning_in_content = params.stream && (reasoning_format == COMMON_REASONING_FORMAT_DEEPSEEK_LEGACY);