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common : change default parameters to pre-#1126 (#1223)
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2 changed files with 25 additions and 25 deletions
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@ -17,7 +17,7 @@
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struct gpt_params {
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int32_t seed = -1; // RNG seed
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int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
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int32_t n_predict = 128; // new tokens to predict
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int32_t n_predict = -1; // new tokens to predict
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int32_t n_parts = -1; // amount of model parts (-1 = determine from model dimensions)
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int32_t n_ctx = 512; // context size
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int32_t n_batch = 512; // batch size for prompt processing (must be >=32 to use BLAS)
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@ -25,18 +25,18 @@ struct gpt_params {
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// sampling parameters
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std::unordered_map<llama_token, float> logit_bias; // logit bias for specific tokens
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int32_t top_k = 0; // <= 0 to use vocab size
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float top_p = 1.0f; // 1.0 = disabled
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float tfs_z = 1.0f; // 1.0 = disabled
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float typical_p = 1.0f; // 1.0 = disabled
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float temp = 1.0f; // 1.0 = disabled
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float repeat_penalty = 1.0f; // 1.0 = disabled
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int32_t repeat_last_n = -1; // last n tokens to penalize (0 = disable penalty, -1 = context size)
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float frequency_penalty = 0.0f; // 0.0 = disabled
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float presence_penalty = 0.0f; // 0.0 = disabled
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int32_t top_k = 40; // <= 0 to use vocab size
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float top_p = 0.95f; // 1.0 = disabled
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float tfs_z = 1.00f; // 1.0 = disabled
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float typical_p = 1.00f; // 1.0 = disabled
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float temp = 0.80f; // 1.0 = disabled
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float repeat_penalty = 1.10f; // 1.0 = disabled
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int32_t repeat_last_n = 64; // last n tokens to penalize (0 = disable penalty, -1 = context size)
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float frequency_penalty = 0.00f; // 0.0 = disabled
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float presence_penalty = 0.00f; // 0.0 = disabled
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int mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0
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float mirostat_tau = 5.0f; // target entropy
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float mirostat_eta = 0.1f; // learning rate
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float mirostat_tau = 5.00f; // target entropy
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float mirostat_eta = 0.10f; // learning rate
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std::string model = "models/lamma-7B/ggml-model.bin"; // model path
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std::string prompt = "";
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