diff --git a/README.md b/README.md index 63728d2..93d0789 100644 --- a/README.md +++ b/README.md @@ -163,9 +163,9 @@ If you are interested in our design principles and the implementation of the inj

Acknowledgment and Contributors

-The development of KTransformer is based on the flexible and versatile framework provided by Transformers. We also benefit from advanced kernels such as GGUF/GGML, Llamafile, Marlin, sglang and flashinfer. We are planning to contribute back to the community by upstreaming our modifications. +The development of KTransformers is based on the flexible and versatile framework provided by Transformers. We also benefit from advanced kernels such as GGUF/GGML, Llamafile, Marlin, sglang and flashinfer. We are planning to contribute back to the community by upstreaming our modifications. -KTransformer is actively maintained and developed by contributors from the MADSys group at Tsinghua University and members from Approaching.AI. We welcome new contributors to join us in making KTransformer faster and easier to use. +KTransformers is actively maintained and developed by contributors from the MADSys group at Tsinghua University and members from Approaching.AI. We welcome new contributors to join us in making KTransformers faster and easier to use.

Discussion

diff --git a/README_ZH.md b/README_ZH.md index 6c82805..48f28e0 100644 --- a/README_ZH.md +++ b/README_ZH.md @@ -152,9 +152,9 @@ YAML 文件中的每个规则都有两部分：`match` 和 `replace`。`match`

致谢和贡献者

-KTransformer 的开发基于 Transformers 提供的灵活和多功能框架。我们还受益于 GGUF/GGML、Llamafile 、 Marlin、sglang和flashinfer 等高级内核。我们计划通过向上游贡献我们的修改来回馈社区。 +KTransformers 的开发基于 Transformers 提供的灵活和多功能框架。我们还受益于 GGUF/GGML、Llamafile 、 Marlin、sglang和flashinfer 等高级内核。我们计划通过向上游贡献我们的修改来回馈社区。 -KTransformer 由清华大学 MADSys group 小组的成员以及 Approaching.AI 的成员积极维护和开发。我们欢迎新的贡献者加入我们，使 KTransformer 更快、更易于使用。 +KTransformers 由清华大学 MADSys group 小组的成员以及 Approaching.AI 的成员积极维护和开发。我们欢迎新的贡献者加入我们，使 KTransformers 更快、更易于使用。

讨论

diff --git a/doc/SUMMARY.md b/doc/SUMMARY.md index 854549c..acdba09 100644 --- a/doc/SUMMARY.md +++ b/doc/SUMMARY.md @@ -1,4 +1,4 @@ -# Ktransformer +# Ktransformers [Introduction](./README.md) # Install diff --git a/doc/en/Docker.md b/doc/en/Docker.md index f31c3b5..ee5072b 100644 --- a/doc/en/Docker.md +++ b/doc/en/Docker.md @@ -9,7 +9,7 @@ There is a Docker image available for our project, you can pull the docker image ``` docker pull approachingai/ktransformers:0.2.1 ``` -**Notice**: In this image, we compile the ktransformers in AVX512 instuction CPUs, if your cpu not support AVX512, it is suggested to recompile and install ktransformer in the /workspace/ktransformers directory within the container. +**Notice**: In this image, we compile the ktransformers in AVX512 instuction CPUs, if your cpu not support AVX512, it is suggested to recompile and install ktransformers in the /workspace/ktransformers directory within the container. ## Building docker image locally - Download Dockerfile in [there](../../Dockerfile) diff --git a/doc/en/FAQ.md b/doc/en/FAQ.md index e001153..991612d 100644 --- a/doc/en/FAQ.md +++ b/doc/en/FAQ.md @@ -118,7 +118,7 @@ From: https://github.com/kvcache-ai/ktransformers/issues/374 1. First, download the latest source code using git. 2. Then, modify the DeepSeek-V3-Chat-multi-gpu-4.yaml in the source code and all related yaml files, replacing all instances of KLinearMarlin with KLinearTorch. -3. Next, you need to compile from the ktransformer source code until it successfully compiles on your local machine. +3. Next, you need to compile from the ktransformers source code until it successfully compiles on your local machine. 4. Then, install flash-attn. It won't be used, but not installing it will cause an error. 5. Then, modify local_chat.py, replacing all instances of flash_attention_2 with eager. 6. Then, run local_chat.py. Be sure to follow the official tutorial's commands and adjust according to your local machine's parameters.