TensorRT-LLMs/examples/llm-api/llm_inference_customize.py
Kaiyu Xie aaacc9bd68
Update TensorRT-LLM (#2562)
* Update TensorRT-LLM

---------

Co-authored-by: Starrick Liu <73152103+StarrickLiu@users.noreply.github.com>
2024-12-11 00:31:05 -08:00

54 lines
2.3 KiB
Python

### Generate text
import tempfile
from tensorrt_llm.hlapi import LLM, BuildConfig, KvCacheConfig, SamplingParams
def main():
# The end user can customize the build configuration with the build_config class and other arguments borrowed from the lower-level APIs
build_config = BuildConfig()
build_config.max_batch_size = 128
build_config.max_num_tokens = 2048
build_config.max_beam_width = 4
# Model could accept HF model name or a path to local HF model.
llm = LLM(
model="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
build_config=build_config,
kv_cache_config=KvCacheConfig(
free_gpu_memory_fraction=0.8
), # Similar to `build_config`, you can also customize the runtime configuration with the `kv_cache_config`, `runtime_config`, `peft_cache_config` or \
# other arguments borrowed from the lower-level APIs.
)
# You can save the engine to disk and load it back later, the LLM class can accept either a HF model or a TRT-LLM engine.
llm.save(tempfile.mkdtemp())
# Sample prompts.
prompts = [
"Hello, my name is",
"The president of the United States is",
"The capital of France is",
"The future of AI is",
]
# With SamplingParams, you can customize the sampling strategy, such as beam search, temperature, and so on.
sampling_params = SamplingParams(temperature=0.8, top_p=0.95, beam_width=4)
for output in llm.generate(prompts, sampling_params):
print(
f"Prompt: {output.prompt!r}, Generated text: {output.outputs[0].text!r}"
)
# Got output like
# Prompt: 'Hello, my name is', Generated text: '\n\nJane Smith. I am a student pursuing my degree in Computer Science at [university]. I enjoy learning new things, especially technology and programming'
# Prompt: 'The president of the United States is', Generated text: 'likely to nominate a new Supreme Court justice to fill the seat vacated by the death of Antonin Scalia. The Senate should vote to confirm the'
# Prompt: 'The capital of France is', Generated text: 'Paris.'
# Prompt: 'The future of AI is', Generated text: 'an exciting time for us. We are constantly researching, developing, and improving our platform to create the most advanced and efficient model available. We are'
if __name__ == '__main__':
main()