mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-13 22:18:36 +08:00
45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
### :section Basics
|
|
### :title Distributed LLM Generation
|
|
### :order 3
|
|
from tensorrt_llm import LLM, SamplingParams
|
|
|
|
|
|
def main():
|
|
# model could accept HF model name or a path to local HF model.
|
|
llm = LLM(
|
|
model="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
|
|
# Enable 2-way tensor parallelism
|
|
tensor_parallel_size=2
|
|
# Enable 2-way pipeline parallelism if needed
|
|
# pipeline_parallel_size=2
|
|
# Enable 2-way expert parallelism for MoE model's expert weights
|
|
# moe_expert_parallel_size=2
|
|
# Enable 2-way tensor parallelism for MoE model's expert weights
|
|
# moe_tensor_parallel_size=2
|
|
)
|
|
|
|
# Sample prompts.
|
|
prompts = [
|
|
"Hello, my name is",
|
|
"The capital of France is",
|
|
"The future of AI is",
|
|
]
|
|
|
|
# Create a sampling params.
|
|
sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
|
|
|
|
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 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'
|
|
|
|
|
|
# The entry point of the program need to be protected for spawning processes.
|
|
if __name__ == '__main__':
|
|
main()
|