kanshan/TensorRT-LLMs
1
0
Fork 0
mirror of https://github.com/NVIDIA/TensorRT-LLM.git synced 2026-01-13 22:18:36 +08:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

Fix the link of doc (#3903)

Browse Source 
Signed-off-by: taoli <litaotju@users.noreply.github.com>
Co-authored-by: taoli <litaotju@users.noreply.github.com>
This commit is contained in:
Tao Li @ NVIDIA 2025-04-28 14:41:40 +08:00 committed by GitHub
parent 82a8e43557
commit 2fe35924e3
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 1 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
examples/models/core/deepseek_v3/README.md
View File

@ -3,7 +3,7 @@
This guide walks you through the examples to run the DeepSeek‑V3/DeepSeek-R1 models using NVIDIA's TensorRT-LLM framework with the PyTorch backend.
**DeepSeek-R1 and DeepSeek-V3 share exact same model architecture other than weights differences, and share same code path in TensorRT-LLM, for brevity we only provide one model example, the example command to be used interchangeablely by only replacing the model name to the other one**.
To benchmark the model with best configurations, refer to [DeepSeek R1 benchmarking blog](../../docs/source/blogs/Best_perf_practice_on_DeepSeek-R1_in_TensorRT-LLM.md).
To benchmark the model with best configurations, refer to [DeepSeek R1 benchmarking blog](../../../../docs/source/blogs/Best_perf_practice_on_DeepSeek-R1_in_TensorRT-LLM.md).
Please refer to [this guide](https://nvidia.github.io/TensorRT-LLM/installation/build-from-source-linux.html) for how to build TensorRT-LLM from source and start a TRT-LLM docker container.