PyTorch Backend#

Note

Note: This feature is currently in beta, and the related API is subjected to change in future versions.

To enhance the usability of the system and improve developer efficiency, TensorRT-LLM launches a new backend based on PyTorch.

The PyTorch backend of TensorRT-LLM is available in version 0.17 and later. You can try it via importing tensorrt_llm._torch.

Quick Start#

Here is a simple example to show how to use tensorrt_llm.LLM API with Llama model.

 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 capital of France is",
14        "The future of AI is",
15    ]
16
17    # Create a sampling params.
18    sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
19
20    for output in llm.generate(prompts, sampling_params):
21        print(
22            f"Prompt: {output.prompt!r}, Generated text: {output.outputs[0].text!r}"
23        )
24
25    # Got output like
26    # 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'
27    # 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'
28    # Prompt: 'The capital of France is', Generated text: 'Paris.'
29    # 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'
30
31
32if __name__ == '__main__':
33    main()

Features#

Developer Guide#

Key Components#

Known Issues#

  • The PyTorch backend on SBSA is incompatible with bare metal environments like Ubuntu 24.04. Please use the PyTorch NGC Container for optimal support on SBSA platforms.

Prototype Features#