Hi 您好,我根据您的代码,对 whisper-large-v3-turbo 这个模型进行编译部署,报错如下,我看 24.09-trtllm-python-py3 支持的 tensorrt-llm 是0.13.0.您那边测试是成功的吗? Traceback (most recent call last): File "/workspace/TensorRT-LLM/examples/whisper/convert_checkpoint.py", line 24, in <module> ...
将编译好的cpp库文件复制到该文件lib文件夹 cp-rP TensorRT-LLM/cpp/build/lib/*.so lib/ python setup.py build python setup.py bdist_wheel pip install dist/tensorrt_llm-0.5.0-py3-none-any.whl -i https://pypi.tuna.tsinghua.edu.cn/simple 3. 构建TRT engine模型 python3 hf_qwen_convert.py ...
cd examples/llama python3 convert_checkpoint.py --model_dir /app/tensorrt_llm/model/Llama-2-7b-hf --dtype float16 --output_dir ./checkpoint_1gpu_fp16 trtllm-build --checkpoint_dir ./checkpoint_1gpu_fp16 --gemm_plugin float16 --output_dir ./engine_lgpu_fp16 python ../run.py --...
export LD_LIBRARY_PATH=/usr/local/lib/python3.10/dist-packages/tensorrt_llm/libs Create a symbolic link ln -s /usr/local/lib/python3.10/dist-packages/tensorrt_llm/libs/libnvinfer_plugin_tensorrt_llm.so /usr/lib/libnvinfer_plugin_tensorrt_llm.so.9 Set the LD_LIBRARY_PATH as follows export ...
python3 tools/fill_template.py --in_place \ all_models/inflight_batcher_llm/preprocessing/config.pbtxt \ tokenizer_type:auto,\ tokenizer_dir:../Phi-3-mini-4k-instruct,\ triton_max_batch_size:128,\ preprocessing_instance_count:2 Update tensorrt_llm/config.pbxt python3 tools/fill_template....
docker pull nvcr.io/nvidia/tritonserver:23.12-trtllm-python-py3 Run image and either clone triton_cli in the container or mount it to the container pip install --no-cache-dir --extra-index-url https://pypi.nvidia.com/ tensorrt-llm==0.7.0 ...
tllm_checkpoint/ \ --output_dir /tmp/Qwen2.5-7B-Instruct/trt_engines/ \ --gemm_plugin bfloat16 --max_batch_size 16 --paged_kv_cacheenable--use_paged_context_fmhaenable\ --max_input_len 32256 --max_seq_len 32768 --max_num_tokens 32256#运行测试python3 ../run.py --input_text"...
nvcr.io/nvidia/tritonserver:24.10-trtllm-python-py3#Clone these changesgit clone -b rmccormick/ux https://github.com/triton-inference-server/tensorrtllm_backend.git#Specify directory for engines and tokenizer config to either be read from, or written toexportTRTLLM_ENGINE_DIR="/tmp/hackathon"...
docker run --runtime=nvidia --gpus all -v ${PWD}:/BentoTRTLLM -v ~/bentoml:/root/bentoml -p 3000:3000 --entrypoint /bin/bash -it --workdir /BentoTRTLLM nvcr.io/nvidia/tritonserver:24.06-trtllm-python-py3 Install the dependencies. pip install -r requirements.txt Start the Service....
154 + python3 client/openai_cli.py 127.0.0.1:9997 "你好,你是谁?" false 155 + # 返回如下: 156 + : ' 157 + ChatCompletion(id='chatcmpl-11', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='我是来自阿里云的大规模语言模型,我叫...