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# llama.cpp/example/parallel
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Simplified simluation for serving incoming requests in parallel
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# llama.cpp/example/simple
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The purpose of this example is to demonstrate a minimal usage of llama.cpp for generating text with a given prompt.
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The example demonstrates single-batch as well as parallel generation.
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## Single-batch generation
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```bash
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./simple ./models/llama-7b-v2/ggml-model-f16.gguf "Hello my name is" 1
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...
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main: n_len = 32, n_ctx = 2048, n_parallel = 1, n_kv_req = 32
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Hello my name is Shawn and I'm a 20 year old male from the United States. I'm a 20 year old
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main: decoded 27 tokens in 2.31 s, speed: 11.68 t/s
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llama_print_timings: load time = 579.15 ms
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llama_print_timings: sample time = 0.72 ms / 28 runs ( 0.03 ms per token, 38888.89 tokens per second)
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llama_print_timings: prompt eval time = 655.63 ms / 10 tokens ( 65.56 ms per token, 15.25 tokens per second)
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llama_print_timings: eval time = 2180.97 ms / 27 runs ( 80.78 ms per token, 12.38 tokens per second)
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llama_print_timings: total time = 2891.13 ms
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```
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## Parallel generation
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```bash
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./simple ./models/llama-7b-v2/ggml-model-f16.gguf "Hello my name is" 4
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...
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main: n_len = 32, n_ctx = 2048, n_parallel = 4, n_kv_req = 113
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Hello my name is
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main: generating 4 sequences ...
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main: stream 0 finished
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main: stream 1 finished
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main: stream 2 finished
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main: stream 3 finished
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sequence 0:
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Hello my name is Shirley. I am a 25-year-old female who has been working for over 5 years as a b
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sequence 1:
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Hello my name is Renee and I'm a 32 year old female from the United States. I'm looking for a man between
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sequence 2:
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Hello my name is Diana. I am looking for a housekeeping job. I have experience with children and have my own transportation. I am
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sequence 3:
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Hello my name is Cody. I am a 3 year old neutered male. I am a very friendly cat. I am very playful and
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main: decoded 108 tokens in 3.57 s, speed: 30.26 t/s
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llama_print_timings: load time = 587.00 ms
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llama_print_timings: sample time = 2.56 ms / 112 runs ( 0.02 ms per token, 43664.72 tokens per second)
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llama_print_timings: prompt eval time = 4089.11 ms / 118 tokens ( 34.65 ms per token, 28.86 tokens per second)
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llama_print_timings: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
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llama_print_timings: total time = 4156.04 ms
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```
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