TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.
Whether it supports the sqlcoder series model, vllm can run sqlcoder directly as starcoder. I'm wondering if this error is related to the model itself?
System Info
nvidia A100 80G centos7 x86_64
Who can help?
@ncomly-nvidia @kaiyux @juney-nvidia
Information
Tasks
examples
folder (such as GLUE/SQuAD, ...)Reproduction
python hf_gpt_convert.py --model starcoder -i ./sqlrcoder -o ./c-model/sqlcoder --tensor-parallelism 1 --storage-type float16
python3 build.py \ --model_dir ./c-model/sqlcoder/1-gpu \ --remove_input_padding \ --use_gpt_attention_plugin \ --enable_context_fmha \ --use_gemm_plugin \ --parallel_build \ --output_dir sqlcoder_outputs_tp1 \
python ../run.py --engine_dir sqlcoder_outputs_tp1 --tokenizer_dir ./sqlcoder --input_text "input text" --max_output_len 200 --no_add_special_tokens
Expected behavior
output sql
actual behavior
additional notes
Whether it supports the sqlcoder series model, vllm can run sqlcoder directly as starcoder. I'm wondering if this error is related to the model itself?