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Unverified Commit 233bbb8c authored by UnicornChan's avatar UnicornChan Committed by GitHub
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Merge pull request #57 from UnicornChan/develop-0.1.3 

[feature] release 0.1.3
parents 67f8b370 4d1d561d
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Showing with 431 additions and 59 deletions
.github/workflows/package_wheel_release.yml
View file @ 233bbb8c
...@@ -29,11 +29,6 @@ jobs: ...@@ -29,11 +29,6 @@ jobs:
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.12', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.12', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '124'} - { os: ubuntu-20.04, pyver: '3.12', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.12', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.12', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.12', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.12', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
...@@ -52,12 +47,6 @@ jobs: ...@@ -52,12 +47,6 @@ jobs:
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
...@@ -76,12 +65,6 @@ jobs: ...@@ -76,12 +65,6 @@ jobs:
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '124'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'FANCY', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: ubuntu-20.04, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: ubuntu-20.04, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
...@@ -98,10 +81,6 @@ jobs: ...@@ -98,10 +81,6 @@ jobs:
- { os: windows-2022, pyver: '3.12', cuda: '12.2.2', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: windows-2022, pyver: '3.12', cuda: '12.2.2', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: windows-2022, pyver: '3.12', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: windows-2022, pyver: '3.12', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: windows-2022, pyver: '3.12', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: windows-2022, pyver: '3.12', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: windows-2022, pyver: '3.12', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '124'}
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- { os: windows-2022, pyver: '3.12', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: windows-2022, pyver: '3.12', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: windows-2022, pyver: '3.12', cuda: '12.1.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: windows-2022, pyver: '3.12', cuda: '12.1.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
...@@ -114,10 +93,6 @@ jobs: ...@@ -114,10 +93,6 @@ jobs:
- { os: windows-2022, pyver: '3.11', cuda: '12.2.2', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: windows-2022, pyver: '3.11', cuda: '12.2.2', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: windows-2022, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: windows-2022, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: windows-2022, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: windows-2022, pyver: '3.11', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: windows-2022, pyver: '3.11', cuda: '12.5.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '124'}
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- { os: windows-2022, pyver: '3.11', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '124'}
- { os: windows-2022, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: windows-2022, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: windows-2022, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: windows-2022, pyver: '3.11', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: windows-2022, pyver: '3.11', cuda: '12.1.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: windows-2022, pyver: '3.11', cuda: '12.1.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
...@@ -130,10 +105,6 @@ jobs: ...@@ -130,10 +105,6 @@ jobs:
- { os: windows-2022, pyver: '3.10', cuda: '12.2.2', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: windows-2022, pyver: '3.10', cuda: '12.2.2', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: windows-2022, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: windows-2022, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: windows-2022, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: windows-2022, pyver: '3.10', cuda: '12.1.1', torch: '2.4.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
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- { os: windows-2022, pyver: '3.10', cuda: '12.4.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '124'}
- { os: windows-2022, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: windows-2022, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
- { os: windows-2022, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'} - { os: windows-2022, pyver: '3.10', cuda: '12.2.2', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX2', torch_cu: '121'}
- { os: windows-2022, pyver: '3.10', cuda: '12.1.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'} - { os: windows-2022, pyver: '3.10', cuda: '12.1.1', torch: '2.3.0', cudaarch: '8.0;8.6;8.7;8.9;9.0+PTX', instruct: 'AVX512', torch_cu: '121'}
...@@ -219,6 +190,11 @@ jobs: ...@@ -219,6 +190,11 @@ jobs:
$env:CUDA_PATH = "$env:CUDA_PATH/Library" $env:CUDA_PATH = "$env:CUDA_PATH/Library"
$env:CUDA_HOME = $env:CUDA_PATH $env:CUDA_HOME = $env:CUDA_PATH
$env:PATH = "$env:CUDA_PATH/bin;" + $env:PATH $env:PATH = "$env:CUDA_PATH/bin;" + $env:PATH
$directory = "$env:CUDA_PATH/lib/x64/"
if (-not (Test-Path -Path $directory)) {
New-Item -ItemType Directory -Path $directory
Write-Output "Directory '$directory' created."
}
cp $env:CUDA_PATH/lib/*.lib $env:CUDA_PATH/lib/x64/ cp $env:CUDA_PATH/lib/*.lib $env:CUDA_PATH/lib/x64/
$env:INCLUDE =$env:CUDA_PATH + "/include/targets/x64;" + $env:INCLUDE $env:INCLUDE =$env:CUDA_PATH + "/include/targets/x64;" + $env:INCLUDE
......
.gitignore
View file @ 233bbb8c
...@@ -18,3 +18,4 @@ compile_commands.json ...@@ -18,3 +18,4 @@ compile_commands.json
ktransformers/server/local_store/ ktransformers/server/local_store/
ktransformers/server_test1.db ktransformers/server_test1.db
*.patch *.patch
local_chat_djw.py
\ No newline at end of file
README.md
View file @ 233bbb8c
...@@ -2,17 +2,16 @@ ...@@ -2,17 +2,16 @@
<!-- <h1>KTransformers</h1> --> <!-- <h1>KTransformers</h1> -->
<p align="center"> <p align="center">
<picture> <picture>
<img alt="KTransformers" src="https://github.com/user-attachments/assets/d5a2492f-a415-4456-af99-4ab102f13f8b" width=50%> <img alt="KTransformers" src="https://github.com/user-attachments/assets/d5a2492f-a415-4456-af99-4ab102f13f8b" width=50%>
</picture> </picture>
</p> </p>
<h3>A Flexible Framework for Experiencing Cutting-edge LLM Inference Optimizations</h3> <h3>A Flexible Framework for Experiencing Cutting-edge LLM Inference Optimizations</h3>
<strong><a href="#show-cases">🔥 Show Cases</a> | <a href="#quick-start">🚀 Quick Start</a> | <a href="#tutorial">📃 Tutorial</a> | <a href="https://github.com/kvcache-ai/ktransformers/discussions">💬 Discussion </a> </strong> <strong><a href="#show-cases">🔥 Show Cases</a> | <a href="#quick-start">🚀 Quick Start</a> | <a href="#tutorial">📃 Tutorial</a> | <a href="https://github.com/kvcache-ai/ktransformers/discussions">💬 Discussion </a> </strong>
</div> </div>
<h2 id="intro">🎉 Introduction</h2> <h2 id="intro">🎉 Introduction</h2>
KTransformers, pronounced as Quick Transformers, is designed to enhance your 🤗 <a href="https://github.com/huggingface/transformers">Transformers</a> experience with advanced kernel optimizations and placement/parallelism strategies. KTransformers, pronounced as Quick Transformers, is designed to enhance your 🤗 <a href="https://github.com/huggingface/transformers">Transformers</a> experience with advanced kernel optimizations and placement/parallelism strategies.
<br/><br/> <br/><br/>
...@@ -22,16 +21,42 @@ interface, RESTful APIs compliant with OpenAI and Ollama, and even a simplified ...@@ -22,16 +21,42 @@ interface, RESTful APIs compliant with OpenAI and Ollama, and even a simplified
<br/><br/> <br/><br/>
Our vision for KTransformers is to serve as a flexible platform for experimenting with innovative LLM inference optimizations. Please let us know if you need any other features. Our vision for KTransformers is to serve as a flexible platform for experimenting with innovative LLM inference optimizations. Please let us know if you need any other features.
<h2 id="Updates">✨ Updates</h2> <h2 id="Updates">🔥 Updates</h2>
* **Aug 28, 2024**: Support 1M context under the InternLM2.5-7B-Chat-1M model, utilizing 24GB of VRAM and 150GB of DRAM.
* **Aug 28, 2024**: Decrease DeepseekV2's required DRAM from 20G to 10G.
* **Aug 15, 2024**: Update detailed [TUTORIAL](doc/en/injection_tutorial.md) for injection and multi-GPU. * **Aug 15, 2024**: Update detailed [TUTORIAL](doc/en/injection_tutorial.md) for injection and multi-GPU.
* **Aug 14, 2024**: Support llamfile as linear backend, * **Aug 14, 2024**: Support llamfile as linear backend.
* **Aug 12, 2024**: Support multiple GPU; Support new model: mixtral 8\*7B and 8\*22B; Support q2k, q3k, q5k dequant on gpu. * **Aug 12, 2024**: Support multiple GPU; Support new model: mixtral 8\*7B and 8\*22B; Support q2k, q3k, q5k dequant on gpu.
* **Aug 9, 2024**: Support windows native. * **Aug 9, 2024**: Support windows native.
<h2 id="show-cases">🔥 Show Cases</h2> <h2 id="show-cases">🔥 Show Cases</h2>
<h3>GPT-4-level Local VSCode Copilot on a Desktop with only 24GB VRAM</h3> <h3>1M Context Local Inference on a Desktop with Only 24GB VRAM</h3>
<p align="center">
https://github.com/user-attachments/assets/a865e5e4-bca3-401e-94b8-af3c080e6c12
* **1M Context InternLM 2.5 7B**: Operates at full bf16 precision, utilizing 24GB VRAM and 150GB DRAM, which is feasible on a local desktop setup. It achieves a 92.88% success rate on the 1M "Needle In a Haystack" test and 100% on the 128K NIAH test.
<p align="center">
<picture>
<img alt="Single Needle Retrieval 128K" src="./doc/assets/needle_128K.png" width=100%>
</picture>
</p>
<p align="center"> <p align="center">
<picture>
<img alt="Single Needle Retrieval 1000K" src="./doc/assets/needle_1M.png" width=100%>
</picture>
</p>
* **Enhanced Speed**: Reaches 16.91 tokens/s for generation with a 1M context using sparse attention, powered by llamafile kernels. This method is over 10 times faster than full attention approach of llama.cpp.
* **Flexible Sparse Attention Framework**: Offers a flexible block sparse attention framework for CPU offloaded decoding. Compatible with SnapKV, Quest, and InfLLm. Further information is available [here](./doc/en/long_context_tutorial.md).
<div>
<h3>GPT-4-level Local VSCode Copilot on a Desktop with only 24GB VRAM</h3>
</div>
https://github.com/user-attachments/assets/0b9fa2da-66f0-48eb-b4b9-f0e1f06f8927 https://github.com/user-attachments/assets/0b9fa2da-66f0-48eb-b4b9-f0e1f06f8927
...@@ -54,7 +79,6 @@ https://github.com/user-attachments/assets/4c6a8a38-05aa-497d-8eb1-3a5b3918429c ...@@ -54,7 +79,6 @@ https://github.com/user-attachments/assets/4c6a8a38-05aa-497d-8eb1-3a5b3918429c
</p> </p>
<strong>More advanced features will coming soon, so stay tuned!</strong> <strong>More advanced features will coming soon, so stay tuned!</strong>
<h2 id="quick-start">🚀 Quick Start</h2> <h2 id="quick-start">🚀 Quick Start</h2>
...@@ -89,17 +113,21 @@ Some preparation: ...@@ -89,17 +113,21 @@ Some preparation:
``` ```
- Linux-x86_64 with gcc, g++ and cmake - Linux-x86_64 with gcc, g++ and cmake
```sh ```sh
sudo apt-get update sudo apt-get update
sudo apt-get install gcc g++ cmake ninja-build sudo apt-get install gcc g++ cmake ninja-build
``` ```
- We recommend using [Conda](https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh) to create a virtual environment with Python=3.11 to run our program. - We recommend using [Conda](https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh) to create a virtual environment with Python=3.11 to run our program.
```sh ```sh
conda create --name ktransformers python=3.11 conda create --name ktransformers python=3.11
conda activate ktransformers # you may need to run ‘conda init’ and reopen shell first conda activate ktransformers # you may need to run ‘conda init’ and reopen shell first
``` ```
- Make sure that PyTorch, packaging, ninja is installed - Make sure that PyTorch, packaging, ninja is installed
``` ```
pip install torch packaging ninja pip install torch packaging ninja
``` ```
...@@ -107,28 +135,36 @@ Some preparation: ...@@ -107,28 +135,36 @@ Some preparation:
<h3>Installation</h3> <h3>Installation</h3>
1. Use a Docker image, see [documentation for Docker](./doc/en/docker.md) 1. Use a Docker image, see [documentation for Docker](./doc/en/docker.md)
2. You can install using Pypi (for linux): 2. You can install using Pypi (for linux):
``` ```
pip install ktransformers --no-build-isolation pip install ktransformers --no-build-isolation
``` ```
for windows we prepare a pre compiled whl package in [ktransformers-0.1.1+cu125torch24avx2-cp311-cp311-win_amd64.whl](https://github.com/kvcache-ai/ktransformers/releases/download/v0.1.1/ktransformers-0.1.1+cu125torch24avx2-cp311-cp311-win_amd64.whl), which require cuda-12.5, torch-2.4, python-3.11, more pre compiled package are being produced. for windows we prepare a pre compiled whl package in [ktransformers-0.1.1+cu125torch24avx2-cp311-cp311-win_amd64.whl](https://github.com/kvcache-ai/ktransformers/releases/download/v0.1.1/ktransformers-0.1.1+cu125torch24avx2-cp311-cp311-win_amd64.whl), which require cuda-12.5, torch-2.4, python-3.11, more pre compiled package are being produced.
3. Or you can download source code and compile: 3. Or you can download source code and compile:
- init source code - init source code
```sh ```sh
git clone https://github.com/kvcache-ai/ktransformers.git git clone https://github.com/kvcache-ai/ktransformers.git
cd ktransformers cd ktransformers
git submodule init git submodule init
git submodule update git submodule update
``` ```
- [Optional] If you want to run with website, please [compile the website](./doc/en/api/server/website.md) before execute ```bash install.sh``` - [Optional] If you want to run with website, please [compile the website](./doc/en/api/server/website.md) before execute ```bash install.sh```
- Compile and install (for Linux) - Compile and install (for Linux)
``` ```
bash install.sh bash install.sh
``` ```
- Compile and install(for Windows) - Compile and install(for Windows)
``` ```
install.bat install.bat
``` ```
...@@ -136,8 +172,7 @@ Some preparation: ...@@ -136,8 +172,7 @@ Some preparation:
<h3>Local Chat</h3> <h3>Local Chat</h3>
We provide a simple command-line local chat Python script that you can run for testing. We provide a simple command-line local chat Python script that you can run for testing.
> Note that this is a very simple test tool only support one round chat without any memory about last input, if you want to try full ability of the model, you may go to [RESTful API and Web UI](#id_666). We use the DeepSeek-V2-Lite-Chat-GGUF model as an example here. But we also support other models, you can replace it with any other model that you want to test. > Note that this is a very simple test tool only support one round chat without any memory about last input, if you want to try full ability of the model, you may go to [RESTful API and Web UI](#id_666). We use the DeepSeek-V2-Lite-Chat-GGUF model as an example here. But we also support other models, you can replace it with any other model that you want to test.
<h4>Run Example</h4> <h4>Run Example</h4>
...@@ -162,23 +197,30 @@ python -m ktransformers.local_chat --model_path deepseek-ai/DeepSeek-V2-Lite-Cha ...@@ -162,23 +197,30 @@ python -m ktransformers.local_chat --model_path deepseek-ai/DeepSeek-V2-Lite-Cha
# python ktransformers.local_chat --model_path ./DeepSeek-V2-Lite --gguf_path ./DeepSeek-V2-Lite-Chat-GGUF # python ktransformers.local_chat --model_path ./DeepSeek-V2-Lite --gguf_path ./DeepSeek-V2-Lite-Chat-GGUF
``` ```
It features the following arguments: It features the following arguments:
- `--model_path` (required): Name of the model (such as "deepseek-ai/DeepSeek-V2-Lite-Chat" which will automatically download configs from [Hugging Face](https://huggingface.co/deepseek-ai/DeepSeek-V2-Lite)). Or if you already got local files you may directly use that path to initialize the model. - `--model_path` (required): Name of the model (such as "deepseek-ai/DeepSeek-V2-Lite-Chat" which will automatically download configs from [Hugging Face](https://huggingface.co/deepseek-ai/DeepSeek-V2-Lite)). Or if you already got local files you may directly use that path to initialize the model.
>Note: <strong>.safetensors</strong> files are not required in the directory. We only need config files to build model and tokenizer.
> Note: <strong>.safetensors</strong> files are not required in the directory. We only need config files to build model and tokenizer.
- `--gguf_path` (required): Path of a directory containing GGUF files which could that can be downloaded from [Hugging Face](https://huggingface.co/mzwing/DeepSeek-V2-Lite-Chat-GGUF/tree/main) (we only support q4_k_m and q8_0 for now, more formats are coming soon). - `--gguf_path` (required): Path of a directory containing GGUF files which could that can be downloaded from [Hugging Face](https://huggingface.co/mzwing/DeepSeek-V2-Lite-Chat-GGUF/tree/main) (we only support q4_k_m and q8_0 for now, more formats are coming soon).
- `--optimize_rule_path` (required except for Qwen2Moe and DeepSeek-V2): Path of YAML file containing optimize rules. There are two rule files pre-written in the [ktransformers/optimize/optimize_rules](ktransformers/optimize/optimize_rules) directory for optimizing DeepSeek-V2 and Qwen2-57B-A14, two SOTA MoE models. - `--optimize_rule_path` (required except for Qwen2Moe and DeepSeek-V2): Path of YAML file containing optimize rules. There are two rule files pre-written in the [ktransformers/optimize/optimize_rules](ktransformers/optimize/optimize_rules) directory for optimizing DeepSeek-V2 and Qwen2-57B-A14, two SOTA MoE models.
- `--max_new_tokens`: Int (default=1000). Maximum number of new tokens to generate. - `--max_new_tokens`: Int (default=1000). Maximum number of new tokens to generate.
- `--cpu_infer`: Int (default=10). The number of CPUs used for inference. Should ideally be set to the (total number of cores - 2). - `--cpu_infer`: Int (default=10). The number of CPUs used for inference. Should ideally be set to the (total number of cores - 2).
<h3 id="supported-model"> Supported Model</h3> <h3 id="supported-model"> Supported Model</h3>
| Model Name | Model Size | VRAM | Minimum DRAM | Recommended DRAM | | Model Name | Model Size | VRAM | Minimum DRAM | Recommended DRAM |
| ---- | ---- | ---- | ---- | ---- | | ------------------------------ | ---------- | ----- | --------------- | ----------------- |
| DeepSeek-V2-q4_k_m | 133G | 24G | 136G | 192G | | DeepSeek-V2-q4_k_m | 133G | 10G | 136G | 192G |
| Qwen2-57B-A14B-Instruct-q4_k_m | 33G | 8G | 34G | 64G | | Qwen2-57B-A14B-Instruct-q4_k_m | 33G | 8G | 34G | 64G |
| DeepSeek-V2-Lite-q4_k_m | 9.7G | 3G | 13G | 16G | | DeepSeek-V2-Lite-q4_k_m | 9.7G | 3G | 13G | 16G |
| Mixtral-8x7B-q4_k_m | 25G | 1.6G | 51G | 64G |
| Mixtral-8x22B-q4_k_m | 80G | 4G | 86.1G | 96G |
| InternLM2.5-7B-Chat-1M | 15.5G | 15.5G | 8G(32K context) | 150G (1M context) |
More will come soon. Please let us know which models you are most interested in. More will come soon. Please let us know which models you are most interested in.
...@@ -188,7 +230,6 @@ Be aware that you need to be subject to their corresponding model licenses when ...@@ -188,7 +230,6 @@ Be aware that you need to be subject to their corresponding model licenses when
<details> <details>
<summary>Click To Show how to run other examples</summary> <summary>Click To Show how to run other examples</summary>
* Qwen2-57B * Qwen2-57B
```sh ```sh
...@@ -208,6 +249,7 @@ python -m ktransformers.local_chat --model_name Qwen/Qwen2-57B-A14B-Instruct --g ...@@ -208,6 +249,7 @@ python -m ktransformers.local_chat --model_name Qwen/Qwen2-57B-A14B-Instruct --g
``` ```
* DeepseekV2 * DeepseekV2
```sh ```sh
mkdir DeepSeek-V2-Chat-0628-GGUF && cd DeepSeek-V2-Chat-0628-GGUF mkdir DeepSeek-V2-Chat-0628-GGUF && cd DeepSeek-V2-Chat-0628-GGUF
# Download weights # Download weights
...@@ -221,8 +263,11 @@ cd .. ...@@ -221,8 +263,11 @@ cd ..
python -m ktransformers.local_chat --model_name deepseek-ai/DeepSeek-V2-Chat-0628 --gguf_path ./DeepSeek-V2-Chat-0628-GGUF python -m ktransformers.local_chat --model_name deepseek-ai/DeepSeek-V2-Chat-0628 --gguf_path ./DeepSeek-V2-Chat-0628-GGUF
# If you see “OSError: We couldn't connect to 'https://huggingface.co' to load this file”, try： # If you see “OSError: We couldn't connect to 'https://huggingface.co' to load this file”, try：
# GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/deepseek-ai/DeepSeek-V2-Chat-0628 # GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/deepseek-ai/DeepSeek-V2-Chat-0628
# python -m ktransformers.local_chat --model_path ./DeepSeek-V2-Chat-0628 --gguf_path ./DeepSeek-V2-Chat-0628-GGUF # python -m ktransformers.local_chat --model_path ./DeepSeek-V2-Chat-0628 --gguf_path ./DeepSeek-V2-Chat-0628-GGUF
``` ```
| model name | weights download link | | model name | weights download link |
...@@ -245,11 +290,15 @@ Start without website: ...@@ -245,11 +290,15 @@ Start without website:
```sh ```sh
ktransformers --model_path deepseek-ai/DeepSeek-V2-Lite-Chat --gguf_path /path/to/DeepSeek-V2-Lite-Chat-GGUF --port 10002 ktransformers --model_path deepseek-ai/DeepSeek-V2-Lite-Chat --gguf_path /path/to/DeepSeek-V2-Lite-Chat-GGUF --port 10002
``` ```
Start with website: Start with website:
```sh ```sh
ktransformers --model_path deepseek-ai/DeepSeek-V2-Lite-Chat --gguf_path /path/to/DeepSeek-V2-Lite-Chat-GGUF --port 10002 --web True ktransformers --model_path deepseek-ai/DeepSeek-V2-Lite-Chat --gguf_path /path/to/DeepSeek-V2-Lite-Chat-GGUF --port 10002 --web True
``` ```
Or you want to start server with transformers, the model_path should include safetensors Or you want to start server with transformers, the model_path should include safetensors
```bash ```bash
ktransformers --type transformers --model_path /mnt/data/model/Qwen2-0.5B-Instruct --port 10002 --web True ktransformers --type transformers --model_path /mnt/data/model/Qwen2-0.5B-Instruct --port 10002 --web True
``` ```
...@@ -264,7 +313,6 @@ Access website with url [http://localhost:10002/web/index.html#/chat](http://loc ...@@ -264,7 +313,6 @@ Access website with url [http://localhost:10002/web/index.html#/chat](http://loc
More information about the RESTful API server can be found [here](doc/en/api/server/server.md). You can also find an example of integrating with Tabby [here](doc/en/api/server/tabby.md). More information about the RESTful API server can be found [here](doc/en/api/server/server.md). You can also find an example of integrating with Tabby [here](doc/en/api/server/tabby.md).
<h2 id="tutorial">📃 Brief Injection Tutorial</h2> <h2 id="tutorial">📃 Brief Injection Tutorial</h2>
At the heart of KTransformers is a user-friendly, template-based injection framework. At the heart of KTransformers is a user-friendly, template-based injection framework.
This allows researchers to easily replace original torch modules with optimized variants. It also simplifies the process of combining multiple optimizations, allowing the exploration of their synergistic effects. This allows researchers to easily replace original torch modules with optimized variants. It also simplifies the process of combining multiple optimizations, allowing the exploration of their synergistic effects.
......
doc/en/long_context_tutorial.md 0 → 100644
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This diff is collapsed.
ktransformers/__init__.py
View file @ 233bbb8c
__version__ = "0.1.2" #!/usr/bin/env python
\ No newline at end of file # coding=utf-8
'''
Description :
Author : kkk1nak0
Date : 2024-08-15 07:34:46
Version : 1.0.0
LastEditors : chenxl
LastEditTime : 2024-08-28 15:19:03
'''
__version__ = "0.1.3"
ktransformers/configs/config.yaml
View file @ 233bbb8c
...@@ -35,3 +35,19 @@ web: ...@@ -35,3 +35,19 @@ web:
ext: ext:
cpu_infer: 10 cpu_infer: 10
long_context:
chunk_size: 4096
max_seq_len: 32000
block_size: 128
local_windows_len: 4096
second_select_num: 32
anchor_type: DYNAMIC
kv_type: FP16
dense_layer_num: 2
anchor_num: 1
preselect_block: True
head_select_mode: SHARED
preselect_block_count: 32
layer_step: 1
token_step: 100
\ No newline at end of file
ktransformers/ktransformers_ext/CMakeLists.txt
View file @ 233bbb8c
cmake_minimum_required(VERSION 3.16) cmake_minimum_required(VERSION 3.16)
project(cpuinfer_ext VERSION 0.1.0) project(cpuinfer_ext VERSION 0.1.0)
set(CMAKE_CXX_STANDARD 17) set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3 -ffast-math") set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3 -ffast-math")
set(CMAKE_BUILD_TYPE "Release") set(CMAKE_BUILD_TYPE "Release")
...@@ -215,7 +216,8 @@ aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR} SOURCE_DIR1) ...@@ -215,7 +216,8 @@ aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR} SOURCE_DIR1)
aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR}/cpu_backend SOURCE_DIR2) aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR}/cpu_backend SOURCE_DIR2)
aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR}/operators/llamafile SOURCE_DIR3) aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR}/operators/llamafile SOURCE_DIR3)
aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR}/../../third_party/llamafile SOURCE_DIR4) aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR}/../../third_party/llamafile SOURCE_DIR4)
set(ALL_SOURCES ${SOURCE_DIR1} ${SOURCE_DIR2} ${SOURCE_DIR3} ${SOURCE_DIR4}) aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR}/operators/kvcache SOURCE_DIR5)
set(ALL_SOURCES ${SOURCE_DIR1} ${SOURCE_DIR2} ${SOURCE_DIR3} ${SOURCE_DIR4} ${SOURCE_DIR5})
message(STATUS "ALL_SOURCES: ${ALL_SOURCES}") message(STATUS "ALL_SOURCES: ${ALL_SOURCES}")
pybind11_add_module(${PROJECT_NAME} MODULE ${ALL_SOURCES}) pybind11_add_module(${PROJECT_NAME} MODULE ${ALL_SOURCES})
...@@ -223,5 +225,8 @@ target_link_libraries(${PROJECT_NAME} PRIVATE llama) ...@@ -223,5 +225,8 @@ target_link_libraries(${PROJECT_NAME} PRIVATE llama)
if(WIN32) if(WIN32)
target_link_libraries(${PROJECT_NAME} PRIVATE "$ENV{CUDA_PATH}/lib/x64/cudart.lib")#CUDA::cudart target_link_libraries(${PROJECT_NAME} PRIVATE "$ENV{CUDA_PATH}/lib/x64/cudart.lib")#CUDA::cudart
elseif(UNIX) elseif(UNIX)
if(NOT DEFINED ENV{CUDA_HOME} OR "$ENV{CUDA_HOME}" STREQUAL "")
set(ENV{CUDA_HOME} "/usr/local/cuda")
endif()
target_link_libraries(${PROJECT_NAME} PRIVATE "$ENV{CUDA_HOME}/lib64/libcudart.so") target_link_libraries(${PROJECT_NAME} PRIVATE "$ENV{CUDA_HOME}/lib64/libcudart.so")
endif() endif()
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