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int main(int argc, char** argv) { | |
auto mymodel = create_mymodel(argc, argv); | |
int N = 10; | |
int max_tgt_len = 500; | |
int n_embd = llama_n_embd(llama_get_model(mymodel->ctx)); | |
// add random float embd to test evaluation | |
float * data = new float[N*n_embd]; | |
std::default_random_engine e; | |
std::uniform_real_distribution<float> u(0,1); | |
for (int i=0;i<N*n_embd;i++) { | |
data[i] = u(e); | |
} | |
eval_string(mymodel, "user: what is the color of the flag of UN?"); | |
eval_float(mymodel, data, N); | |
eval_string(mymodel, "assistant:"); | |
eval_string(mymodel, mymodel->params.prompt.c_str()); | |
const char* tmp; | |
for (int i=0; i<max_tgt_len; i++) { | |
tmp = sampling(mymodel); | |
if (strcmp(tmp, "</s>")==0) break; | |
printf("%s", tmp); | |
fflush(stdout); | |
} | |
printf("\n"); | |
free_mymodel(mymodel); | |
return 0; | |
} | |