Generate text#

Source NVIDIA/TensorRT-LLM.

 1from tensorrt_llm import LLM, SamplingParams
 2
 3
 4def main():
 5
 6    # Model could accept HF model name, a path to local HF model,
 7    # or TensorRT Model Optimizer's quantized checkpoints like nvidia/Llama-3.1-8B-Instruct-FP8 on HF.
 8    llm = LLM(model="TinyLlama/TinyLlama-1.1B-Chat-v1.0")
 9
10    # Sample prompts.
11    prompts = [
12        "Hello, my name is",
13        "The president of the United States is",
14        "The capital of France is",
15        "The future of AI is",
16    ]
17
18    # Create a sampling params.
19    sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
20
21    for output in llm.generate(prompts, sampling_params):
22        print(
23            f"Prompt: {output.prompt!r}, Generated text: {output.outputs[0].text!r}"
24        )
25
26    # Got output like
27    # 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'
28    # 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'
29    # Prompt: 'The capital of France is', Generated text: 'Paris.'
30    # 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'
31
32
33if __name__ == '__main__':
34    main()