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-rw-r--r--examples/perplexity/perplexity.cpp8
1 files changed, 4 insertions, 4 deletions
diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp
index 6870a11..62433e9 100644
--- a/examples/perplexity/perplexity.cpp
+++ b/examples/perplexity/perplexity.cpp
@@ -153,7 +153,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
}
size_t hs_task_count = prompt_lines.size()/6;
- fprintf(stderr, "%s : loaded %lu tasks from prompt.\n", __func__, hs_task_count);
+ fprintf(stderr, "%s : loaded %zu tasks from prompt.\n", __func__, hs_task_count);
// This is needed as usual for LLaMA models
bool prepend_bos = true;
@@ -178,7 +178,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
double ending_logprob[4];
};
- fprintf(stderr, "%s : selecting %lu %s tasks.\n", __func__, hs_task_count, (randomize_tasks?"randomized":"the first") );
+ fprintf(stderr, "%s : selecting %zu %s tasks.\n", __func__, hs_task_count, (randomize_tasks?"randomized":"the first") );
// Select and read data from prompt lines
hs_data_t *hs_data = new hs_data_t[hs_task_count];
@@ -223,7 +223,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
// Stop if query wont fit the ctx window
if (query_size > (size_t)params.n_ctx) {
- fprintf(stderr, "%s : number of tokens in query %lu > n_ctxl\n", __func__, query_size);
+ fprintf(stderr, "%s : number of tokens in query %zu > n_ctxl\n", __func__, query_size);
return;
}
@@ -284,7 +284,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
}
// Print the accumulated accuracy mean x 100
- printf("%li\t%.8lf\n",task_idx+1, acc/double(task_idx+1)*100.0);
+ printf("%zu\t%.8lf\n",task_idx+1, acc/double(task_idx+1)*100.0);
fflush(stdout);
}