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807b0c49ff
* llama : add inference support and model types for T5 and FLAN-T5 model families * llama : add new API functions to support encoder-decoder models: llama_encode(), llama_model_has_encoder(), llama_model_decoder_start_token() * common, llama-cli, llama-batched : add support for encoder-decoder models * convert-hf : handle shared token embeddings tensors in T5Model * convert-hf : add support for SentencePiece BPE tokenizer in T5Model (for Pile-T5 models) * convert-hf : add MT5ForConditionalGeneration and UMT5ForConditionalGeneration to architectures supported by T5Model * convert : add t5 tokenizer tests, use "slow" HF tokenizer for t5 --------- Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> |
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| .. | ||
| batched.cpp | ||
| CMakeLists.txt | ||
| 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