ModelRunnerCpp使用 可以参考示例:https://github.com/NVIDIA/TensorRT-LLM/blob/main/examples/summarize.py # 初始化ModelRunnerCppiftest_trt_llm:ifnotPYTHON_BINDINGSandnotargs.use_py_session:logger.warning("Python bindings of C++ session is unavailable, fallback to Python session.")args.use_py_sessio...
依据args.use_py_session 来选择使用 TRT-LLM python session 还是 cpp session ModelRunner --- python ModelRunnerCpp --- cpp runner_cls = ModelRunner if args.use_py_session else ModelRunnerCpp runner_kwargs = dict(engine_dir=args.engine_dir, lora_dir=args.lora_dir, rank=runtime_rank, debu...
# 准备定长2048 token输入,定长128输出cd TensorRT-LLM/benchmarks/cpppython3 prepare_dataset.py \ --output ./tokens-fixed-lengths.json \ --tokenizer PATH-TO/internlm2-chat-20b/ \ token-norm-dist \ --num-requests 512 \ --input-mean 2048 --input-stdev 0 \ --output-mean 128 --output-...
一般来说,LLM的推理可以直接使用PyTorch代码、使用VLLM/XInference/FastChat等框架,也可以使用llama.cpp/chatglm.cpp/qwen.cpp等c++推理框架。 汀丶人工智能 2024/05/28 12.5K0 LLM推理后端性能大比拼,来自BentoML团队的深度评估! LLM后端量化模型性能 选择适宜的推理后端来服务大型语言模型 (LLMs) 至关重要。它...
因为在尝试做部署与推理Llama3-8B-Chinese-Chat模型的过程中遇到了一个暂时未解决的问题,具体报错为:RuntimeError: 【TensorRT-LLM】【ERROR】 Assertion failed: mpiSize == tp * pp (/home/jenkins/agent/workspace/LLM/release-0.10/L0_PostMerge/tensorrt_llm/cpp/tensorrt_llm/runtime/worldConfig.cpp:99)...
(这里为什么没有用最新的Llama3是因为在尝试做部署与推理Llama3-8B-Chinese-Chat模型的过程中遇到了一个暂时未解决的问题,具体报错为:RuntimeError: 【TensorRT-LLM】【ERROR】 Assertion failed: mpiSize == tp * pp (/home/jenkins/agent/workspace/LLM/release-0.10/L0_PostMerge/tensorrt_llm/cpp/tensorrt_...
# Only CPP session (using executor as low-level API) is supported, while Python session (--use_py_session) is not supported. # Run with Llama 3.3 70B target model mpirun -n 1 --allow-run-as-root python3 ./run.py \ --tokenizer_dir <path to draft model repo> \ --draft_engine...
TRT-LLM默认支持kv-cache，支持PagedAttention，支持flashattention，支持MHA/MQA/GQA等。在cpp下，TRT-LLM实现了许多llm场景下的高性能cuda kernel，并基于TensorRT的plugin机制，支持各种算子调用。与hugging face transformers（HF）相比，TRT-LLM在性能上提升2~3倍左右。TRT-LLM易用性很强，可能与其LLM...
/usr/local/lib/python3.10/dist-packages/tensorrt_llm/runtime/generation.py:881: UserWarning: The PyTorch API of nested tensorsisinprototype stage and will changeinthe near future. (Triggered internally at /opt/pytorch/pytorch/aten/src/ATen/NestedTensorImpl.cpp:178.) ...
The plugins are nodes inserted in the network graph definition that map to user-defined GPU kernels. TensorRT-LLM uses a number of such plugins. They can be found in the cpp/tensorrt_llm/plugins directory. Plugins are written in C++ and...