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authorJohannes Gäßler <johannesg@5d6.de>2023-05-13 15:38:36 +0200
committerGitHub <noreply@github.com>2023-05-13 16:38:36 +0300
commit905d87b70aa189623d500a28602d7a3a755a4769 (patch)
tree11f0d435ecb7555734b14b7a8994e88772bf8190 /examples/common.h
parentf954edda935a70a14cf0cc45ecc7fe7d60cf3e4b (diff)
ggml : GPU-accelerated token generation (#1412)
* CUDA kernel for q4_0 dequant. + mat. vec. mult. * Added q4_1 via template * Added missing __syncthreads(); * --gpu_layers -> --gpu-layers * Shorter dequantize_mul_mat_vec line * q5_0 dequantize_mul_mat kernel * More readable dequantize_mul_mat_vec logic * dequantize_mul_mat_vec kernels for q5_1, q8_0, f16 * llama : offload "output" tensor to GPU too + coding style fixes --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Diffstat (limited to 'examples/common.h')
-rw-r--r--examples/common.h11
1 files changed, 6 insertions, 5 deletions
diff --git a/examples/common.h b/examples/common.h
index 499671b2..717838f0 100644
--- a/examples/common.h
+++ b/examples/common.h
@@ -21,13 +21,14 @@
int32_t get_num_physical_cores();
struct gpt_params {
- int32_t seed = -1; // RNG seed
+ int32_t seed = -1; // RNG seed
int32_t n_threads = get_num_physical_cores();
int32_t n_predict = -1; // new tokens to predict
- int32_t n_parts = -1; // amount of model parts (-1 = determine from model dimensions)
- int32_t n_ctx = 512; // context size
- int32_t n_batch = 512; // batch size for prompt processing (must be >=32 to use BLAS)
- int32_t n_keep = 0; // number of tokens to keep from initial prompt
+ int32_t n_parts = -1; // amount of model parts (-1 = determine from model dimensions)
+ int32_t n_ctx = 512; // context size
+ int32_t n_batch = 512; // batch size for prompt processing (must be >=32 to use BLAS)
+ int32_t n_keep = 0; // number of tokens to keep from initial prompt
+ int32_t n_gpu_layers = 0; // number of layers to store in VRAM
// sampling parameters
std::unordered_map<llama_token, float> logit_bias; // logit bias for specific tokens