common.h : add hellaswag / remove perplexity-lines
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1 changed files with 4 additions and 2 deletions
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@ -70,7 +70,10 @@ struct gpt_params {
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std::string lora_adapter = ""; // lora adapter path
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std::string lora_adapter = ""; // lora adapter path
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std::string lora_base = ""; // base model path for the lora adapter
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std::string lora_base = ""; // base model path for the lora adapter
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bool low_vram = false; // if true, reduce VRAM usage at the cost of performance
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bool hellaswag = false; // compute HellaSwag score over random examples from datafile supplied in prompt
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size_t hellaswag_tasks = 200; // number of examples to use when computing the HellaSwag score
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bool low_vram = false; // if true, reduce VRAM usage at the cost of performance
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bool memory_f16 = true; // use f16 instead of f32 for memory kv
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bool memory_f16 = true; // use f16 instead of f32 for memory kv
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bool random_prompt = false; // do not randomize prompt if none provided
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bool random_prompt = false; // do not randomize prompt if none provided
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bool use_color = false; // use color to distinguish generations and inputs
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bool use_color = false; // use color to distinguish generations and inputs
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@ -86,7 +89,6 @@ struct gpt_params {
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bool instruct = false; // instruction mode (used for Alpaca models)
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bool instruct = false; // instruction mode (used for Alpaca models)
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bool penalize_nl = true; // consider newlines as a repeatable token
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bool penalize_nl = true; // consider newlines as a repeatable token
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bool perplexity = false; // compute perplexity over the prompt
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bool perplexity = false; // compute perplexity over the prompt
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bool perplexity_lines = false; // compute perplexity over each line of the prompt
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bool use_mmap = true; // use mmap for faster loads
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bool use_mmap = true; // use mmap for faster loads
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bool use_mlock = false; // use mlock to keep model in memory
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bool use_mlock = false; // use mlock to keep model in memory
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bool mem_test = false; // compute maximum memory usage
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bool mem_test = false; // compute maximum memory usage
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