llama.cpp/examples/simple
Georgi Gerganov 0e89203b51
speculative : add tree-based sampling example (#3624)
* sampling : one sequence per sampling context

ggml-ci

* speculative : add tree-based sampling support

ggml-ci

* speculative : reuse the n_parallel CLI param

* speculative : refactor sampling

* examples : fix build after sampling refactoring

ggml-ci

* batched : fix n_seq_id

* sampling : fix malloc

ggml-ci

* swift : fix build

ggml-ci

* swift : try to fix build

ggml-ci

* prompts : add assistant.txt

* common : add llama_batch_add() and llama_batch_clear() helpers

* speculative : minor refactor

ggml-ci

* minor : comments + rename

ggml-ci

* speculative : fix off-by-one for n_drafted

* speculative : fix the n_drafted fix + p constants
2023-10-18 16:21:57 +03:00
..
CMakeLists.txt examples : add compiler version and target to build info (#2998) 2023-09-15 16:59:49 -04:00
README.md llama : custom attention mask + parallel decoding + no context swaps (#3228) 2023-09-28 19:04:36 +03:00
simple.cpp speculative : add tree-based sampling example (#3624) 2023-10-18 16:21:57 +03:00

llama.cpp/example/simple

The purpose of this example is to demonstrate a minimal usage of llama.cpp for generating text with a given prompt.

./simple ./models/llama-7b-v2/ggml-model-f16.gguf "Hello my name is"

...

main: n_len = 32, n_ctx = 2048, n_parallel = 1, n_kv_req = 32

 Hello my name is Shawn and I'm a 20 year old male from the United States. I'm a 20 year old

main: decoded 27 tokens in 2.31 s, speed: 11.68 t/s

llama_print_timings:        load time =   579.15 ms
llama_print_timings:      sample time =     0.72 ms /    28 runs   (    0.03 ms per token, 38888.89 tokens per second)
llama_print_timings: prompt eval time =   655.63 ms /    10 tokens (   65.56 ms per token,    15.25 tokens per second)
llama_print_timings:        eval time =  2180.97 ms /    27 runs   (   80.78 ms per token,    12.38 tokens per second)
llama_print_timings:       total time =  2891.13 ms