}
#ifdef GGML_USE_CUBLAS
-#define LLAMA_BACKEND_OFFLOAD GGML_BACKEND_CUDA
+#define LLAMA_BACKEND_OFFLOAD GGML_BACKEND_GPU
#else
#define LLAMA_BACKEND_OFFLOAD GGML_BACKEND_CPU
#endif
layer.w2 = ml->get_tensor(layers_i + ".feed_forward.w2.weight", { n_ff, n_embd}, backend);
layer.w3 = ml->get_tensor(layers_i + ".feed_forward.w3.weight", {n_embd, n_ff}, backend);
- if (backend == GGML_BACKEND_CUDA) {
+ if (backend == GGML_BACKEND_GPU) {
vram_total +=
ggml_nbytes(layer.attention_norm) + ggml_nbytes(layer.wq) + ggml_nbytes(layer.wk) +
ggml_nbytes(layer.wv) + ggml_nbytes(layer.wo) + ggml_nbytes(layer.attention_norm) +
}
}
for (llama_load_tensor & lt : ml->tensors_map.tensors) {
- if (lt.ggml_tensor->backend != GGML_BACKEND_CUDA) {
+ if (lt.ggml_tensor->backend != GGML_BACKEND_GPU) {
continue;
}
if (progress_callback) {