vbatts/llama.cpp
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llama : minor

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Georgi Gerganov 2024-03-10 17:55:32 +02:00
parent 8ee58929fc
commit ecad2afbdd
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1 changed files with 2 additions and 1 deletions
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llama.cpp
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@ -3940,6 +3940,7 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
LLAMA_LOG_INFO("%s: n_ff = %u\n", __func__, hparams.n_ff);
LLAMA_LOG_INFO("%s: n_expert = %u\n", __func__, hparams.n_expert);
LLAMA_LOG_INFO("%s: n_expert_used = %u\n", __func__, hparams.n_expert_used);
LLAMA_LOG_INFO("%s: causal attm = %d\n", __func__, hparams.causal_attn);
LLAMA_LOG_INFO("%s: pooling type = %d\n", __func__, hparams.pooling_type);
LLAMA_LOG_INFO("%s: rope type = %d\n", __func__, hparams.rope_type);
LLAMA_LOG_INFO("%s: rope scaling = %s\n", __func__, rope_scaling_type);
@ -8539,7 +8540,6 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
);
// NOTE: hparams.causal_attn indicates the model is capable of generation and uses the kv cache.
// But if cparams.embeddings is set, the attention will be non-causal nonetheless.
if (cparams.causal_attn) {
const int64_t n_kv = kv_self.n;
const int64_t n_tokens = batch.n_tokens;
@ -12747,6 +12747,7 @@ struct llama_context * llama_new_context_with_model(
}
cparams.causal_attn = hparams.causal_attn;
if (cparams.pooling_type == LLAMA_POOLING_TYPE_UNSPECIFIED) {
if (hparams.pooling_type == LLAMA_POOLING_TYPE_UNSPECIFIED) {
cparams.pooling_type = LLAMA_POOLING_TYPE_NONE;