Below is an example of how to serve a TensorRT-LLM model with the Triton TensorRT-LLM Backend on a 4-GPU environment. The example uses the GPT model from the TensorRT-LLM repository with the NGC Triton TensorRT-LLM container. Make sure you are cloning the same version of TensorRT-LLM ...
The Triton TensorRT-LLM Backend. Contribute to triton-inference-server/tensorrtllm_backend development by creating an account on GitHub.
The Triton TensorRT-LLM Backend. Contribute to uglabs/tensorrtllm_backend development by creating an account on GitHub.
cd tensorrtllm_backend git config submodule.tensorrt_llm.url https://github.com/NVIDIA/TensorRT-LLM.git git submodule update --init --recursive 2.修改文件 在构建的过程中可能会涉及网络的问题,我这里是修改了下面的几个文件 1)build_wheel.py 路径tensorrtllm_backend/tensorrt_llm/scripts/build_wheel....
#相关issue可见:https://github.com/triton-inference-server/tensorrtllm_backend/issues/246 结论:除了0.5.0(这里强调TensorRT-LLM和tensorrtllm_backend版本一致,都是同一分支号),搭配23.10的NGC可以正常work,其他搭配都出错,哪怕是用TensorRT-LLM文件路径下的.so文件替换/opt/tritonserver/backend/tensorrtllm也无法正...
然后克隆https://github.com/triton-inference-server/tensorrtllm_backend: 执行以下命令: cdtensorrtllm_backend mkdirtriton_model_repo #拷贝出来模板模型文件夹 cp-rall_models/inflight_batcher_llm/*triton_model_repo/ #将刚才生成好的`/work/trtModel/llama/1-gpu`移动到模板模型文件夹中 ...
首先,可使用 Dockerfile 在容器中为 Triton 推理服务器构建 TensorRT-LLM 后端。 cd .. git clone-b release/0.5.0 git@github.com:triton-inference-server/tensorrtllm_backend.git cd tensorrtllm_backend git submodule update--init--recursive git lfs install ...
git clone -b v0.9.0 https://github.com/NVIDIA/TensorRT-LLM.git cd TensorRT-LLM git lfs install # 在加载模型前,需要先将模型格式转为TensorRT-LLM的checkpoint格式 cd examples/llama/ python3 convert_checkpoint.py --model_dir /data/llama-2-7b-ckpt --output_dir llama-2-7b-ckpt-f16 --dtype...
git clone https://github.com/triton-inference-server/tensorrtllm_backend 在tensorrtllm_backend项目中tensor_llm目录中拉取TensorRT-LLM项目代码 代码语言:javascript 代码运行次数:0 复制 Cloud Studio代码运行 git clone https://github.com/NVIDIA/TensorRT-LLM.git ...
git clone -b v0.8.0 https://github.com/triton-inference-server/tensorrtllm_backend.git cd tensorrtllm_backend cp ../TensorRT-LLM/tmp/llama/8B/trt_engines/bf16/1-gpu/* all_models/inflight_batcher_llm/tensorrt_llm/1/ 接下来,我们必须使用编译模型引擎的位置修改...