llama.cpp/examples/batched
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
..
batched.cpp speculative : add tree-based sampling example (#3624) 2023-10-18 16:21:57 +03:00
CMakeLists.txt llama : custom attention mask + parallel decoding + no context swaps (#3228) 2023-09-28 19:04:36 +03:00
README.md llama : custom attention mask + parallel decoding + no context swaps (#3228) 2023-09-28 19:04:36 +03:00

llama.cpp/example/batched

The example demonstrates batched generation from a given prompt

./batched ./models/llama-7b-v2/ggml-model-f16.gguf "Hello my name is" 4

...

main: n_len = 32, n_ctx = 2048, n_parallel = 4, n_kv_req = 113

 Hello my name is

main: generating 4 sequences ...

main: stream 0 finished
main: stream 1 finished
main: stream 2 finished
main: stream 3 finished

sequence 0:

Hello my name is Shirley. I am a 25-year-old female who has been working for over 5 years as a b

sequence 1:

Hello my name is Renee and I'm a 32 year old female from the United States. I'm looking for a man between

sequence 2:

Hello my name is Diana. I am looking for a housekeeping job. I have experience with children and have my own transportation. I am

sequence 3:

Hello my name is Cody. I am a 3 year old neutered male. I am a very friendly cat. I am very playful and

main: decoded 108 tokens in 3.57 s, speed: 30.26 t/s

llama_print_timings:        load time =   587.00 ms
llama_print_timings:      sample time =     2.56 ms /   112 runs   (    0.02 ms per token, 43664.72 tokens per second)
llama_print_timings: prompt eval time =  4089.11 ms /   118 tokens (   34.65 ms per token,    28.86 tokens per second)
llama_print_timings:        eval time =     0.00 ms /     1 runs   (    0.00 ms per token,      inf tokens per second)
llama_print_timings:       total time =  4156.04 ms