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ox696c
ktransformers
Commits
2d3aaef8
Unverified
Commit
2d3aaef8
authored
May 14, 2025
by
wang jiahao
Committed by
GitHub
May 14, 2025
Browse files
Merge pull request #1301 from kvcache-ai/update-readme
update readme
parents
ee524b0f
d35d61f6
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doc/en/balance-serve.md
doc/en/balance-serve.md
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doc/en/install.md
doc/en/install.md
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doc/en/llama4.md
doc/en/llama4.md
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doc/zh/DeepseekR1_V3_tutorial_zh.md
doc/zh/DeepseekR1_V3_tutorial_zh.md
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doc/en/balance-serve.md
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2d3aaef8
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@@ -100,8 +100,10 @@ git submodule update --init --recursive
# Install single NUMA dependencies
USE_BALANCE_SERVE
=
1 bash ./install.sh
pip
install
third_party/custom_flashinfer/
# For those who have two cpu and 1T RAM(Dual NUMA):
USE_BALANCE_SERVE
=
1
USE_NUMA
=
1 bash ./install.sh
pip
install
third_party/custom_flashinfer/
```
## Running DeepSeek-R1-Q4KM Models
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doc/en/install.md
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2d3aaef8
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@@ -117,11 +117,13 @@ Download source code and compile:
```shell
USE_BALANCE_SERVE=1 bash ./install.sh
pip install third_party/custom_flashinfer/
```
-
For Multi-concurrency with two cpu and 1T RAM:
```shell
USE_BALANCE_SERVE=1 USE_NUMA=1 bash ./install.sh
pip install third_party/custom_flashinfer/
```
-
For Windows (Windows native temporarily deprecated, please try WSL)
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doc/en/llama4.md
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2d3aaef8
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@@ -68,8 +68,10 @@ pip3 install torch torchvision torchaudio --index-url https://download.pytorch.o
```
bash
# Install single NUMA dependencies
USE_BALANCE_SERVE
=
1 bash ./install.sh
pip
install
third_party/custom_flashinfer/
# For those who have two cpu and 1T RAM(Dual NUMA):
USE_BALANCE_SERVE
=
1
USE_NUMA
=
1 bash ./install.sh
pip
install
third_party/custom_flashinfer/
```
### 4. Use our custom config.json
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doc/zh/DeepseekR1_V3_tutorial_zh.md
View file @
2d3aaef8
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@@ -127,8 +127,10 @@ cd ktransformers
git submodule update
--init
--recursive
# 如果使用双 numa 版本
USE_BALANCE_SERVE
=
1
USE_NUMA
=
1 bash ./install.sh
pip
install
third_party/custom_flashinfer/
# 如果使用单 numa 版本
USE_BALANCE_SERVE
=
1 bash ./install.sh
pip
install
third_party/custom_flashinfer/
# 启动命令
python ktransformers/server/main.py
--model_path
<your model path>
--gguf_path
<your gguf path>
--cpu_infer
62
--optimize_config_path
<inject rule path>
--port
10002
--chunk_size
256
--max_new_tokens
1024
--max_batch_size
4
--port
10002
--cache_lens
32768
--backend_type
balance_serve
```
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