mirror of https://github.com/ggerganov/llama.cpp.git synced 2024-12-26 19:34:35 +00:00

History

Georgi Gerganov d9d54e498d speculative : refactor and add a simpler example (#10362 ) * speculative : refactor and add a simpler example ggml-ci * speculative : clean-up and add comments and TODOs [no ci] * speculative : manage context in common_speculative ggml-ci * speculative : simplify ggml-ci * speculative : simplify (cont) ggml-ci * speculative : add --draft-min CLI arg * speculative : minor fixup * make : build fixes * speculative : do not redraft previous drafts ggml-ci * speculative : fix the draft sampling ggml-ci * speculative : fix compile warning * common : refactor args ggml-ci * common : change defaults [no ci] * common : final touches ggml-ci		2024-11-25 09:58:41 +02:00
..
batched.cpp	speculative : refactor and add a simpler example (#10362 )	2024-11-25 09:58:41 +02:00
CMakeLists.txt	`build`: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809 )	2024-06-13 00:41:52 +01:00
README.md	`build`: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809 )	2024-06-13 00:41:52 +01:00

README.md

llama.cpp/example/batched

The example demonstrates batched generation from a given prompt

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