修改环境搭建方法#1758

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Merged
vansin merged 2 commits into from
Aug 22, 2024
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修改环境搭建方法 #1758

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39 changes: 24 additions & 15 deletions docs/EasterEgg/Android/readme.md
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,7 +29,7 @@ tar -xvzf android-studio-2024.1.1.12-linux.tar.gz
cd android-studio
wget https://dl.google.com/android/repository/commandlinetools-linux-11076708_latest.zip?hl=zh-cn
unzip commandlinetools-linux-11076708_latest.zip\?hl\=zh-cn
export JAVA_HOME=/root/Downloads/android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;android-34" "build-tools;33.0.1" --sdk_root='sdk'
```

Expand All@@ -39,24 +39,22 @@ cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;andr
. "$HOME/.cargo/env"
export ANDROID_NDK=/root/android/android-studio/sdk/ndk/27.0.12077973
export TVM_NDK_CC=$ANDROID_NDK/toolchains/llvm/prebuilt/linux-x86_64/bin/aarch64-linux-android24-clang
export JAVA_HOME=/root/android//android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
export ANDROID_HOME=/root/android/android-studio/sdk
export PATH=/usr/local/cuda-12/bin:$PATH
export PATH=/root/android/android-studio/sdk/cmake/3.22.1/bin:$PATH
```
## 2 转换模型
### 2.1 安装mlc-llm
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)
（如果下载很慢可以取消重新运行一下，或者本地下载了拷过去）
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)，安装`mlc-llm`可能**需要代理**

安装`pytorch`部分也可以使用其他包含`torch`的`conda`环境
```
conda create --name mlc-prebuilt python=3.11
conda activate mlc-prebuilt
conda install -c conda-forge git-lfs
pip install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 transformers sentencepiece protobuf
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
python -m pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightly-cu122 mlc-ai-nightly-cu122
```
测试如下输出说明安装正确

Expand All@@ -72,17 +70,24 @@ cd mlc-llm
git submodule update --init --recursive
```

### 2.2 转换参数
### 2.2 (可选)转换参数
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `convert_weight` 对模型参数进行转换和量化，转换后的参数可以跨平台使用

```
mkdir -p /root/models/
ln -s /share/new_models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat /root/models/internlm2_5-1_8b-chat
cd android/MLCChat
export TVM_SOURCE_DIR=/root/android/mlc-llm/3rdparty/tvm
export MLC_LLM_SOURCE_DIR=/root/android/mlc-llm
mlc_llm convert_weight /root/models/internlm2_5-1_8b-chat/ \
--quantization q4f16_1 \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
```
### 2.3 生成配置
### 2.3 (可选)生成配置
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `gen_config` 生成 `mlc-chat-config.json` 并处理 `tokenizer`

出现提示时输入`y`
Expand All@@ -94,12 +99,16 @@ mlc_llm gen_config /root/models/internlm2_5-1_8b-chat/ \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
Do you wish to run the custom code? [y/N] y
```
### 2.4 上传到huggingface
上传这一步需要能访问huggingface，可能需要部署代理
如果没有代理可以直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
### 2.4 (可选)上传到huggingface
上传这一步需要能访问huggingface，可能需要**部署代理**并耗费一定流量

具体方法可以参考网上的大量教程

如果不想上传到huggingface可以跳过这一步，直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
[https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC](https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC)
### 2.5 (可选) 测试转换的模型
### 2.5 (可选) 测试转换的模型
在打包之前可以测试模型效果，需要编译成二进制文件

在个人电脑上运行测试代码正常，**InternStudio**上**暂未成功**
```

Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks"); } } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); } })(); (function(){ try { var __m = "github.com"; var __re = new RegExp('^' + "github\\.com" + '
Skip to content

修改环境搭建方法#1758

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Merged
vansin merged 2 commits into from
Aug 22, 2024
Merged

修改环境搭建方法 #1758

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
2ee570d
修改环境搭建方法
qew21 Aug 22, 2024
8e12dde
add model link
qew21 Aug 22, 2024
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39 changes: 24 additions & 15 deletions docs/EasterEgg/Android/readme.md
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,7 +29,7 @@ tar -xvzf android-studio-2024.1.1.12-linux.tar.gz
cd android-studio
wget https://dl.google.com/android/repository/commandlinetools-linux-11076708_latest.zip?hl=zh-cn
unzip commandlinetools-linux-11076708_latest.zip\?hl\=zh-cn
export JAVA_HOME=/root/Downloads/android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;android-34" "build-tools;33.0.1" --sdk_root='sdk'
```

Expand All@@ -39,24 +39,22 @@ cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;andr
. "$HOME/.cargo/env"
export ANDROID_NDK=/root/android/android-studio/sdk/ndk/27.0.12077973
export TVM_NDK_CC=$ANDROID_NDK/toolchains/llvm/prebuilt/linux-x86_64/bin/aarch64-linux-android24-clang
export JAVA_HOME=/root/android//android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
export ANDROID_HOME=/root/android/android-studio/sdk
export PATH=/usr/local/cuda-12/bin:$PATH
export PATH=/root/android/android-studio/sdk/cmake/3.22.1/bin:$PATH
```
## 2 转换模型
### 2.1 安装mlc-llm
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)
（如果下载很慢可以取消重新运行一下，或者本地下载了拷过去）
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)，安装`mlc-llm`可能**需要代理**

安装`pytorch`部分也可以使用其他包含`torch`的`conda`环境
```
conda create --name mlc-prebuilt python=3.11
conda activate mlc-prebuilt
conda install -c conda-forge git-lfs
pip install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 transformers sentencepiece protobuf
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
python -m pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightly-cu122 mlc-ai-nightly-cu122
```
测试如下输出说明安装正确

Expand All@@ -72,17 +70,24 @@ cd mlc-llm
git submodule update --init --recursive
```

### 2.2 转换参数
### 2.2 (可选)转换参数
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `convert_weight` 对模型参数进行转换和量化，转换后的参数可以跨平台使用

```
mkdir -p /root/models/
ln -s /share/new_models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat /root/models/internlm2_5-1_8b-chat
cd android/MLCChat
export TVM_SOURCE_DIR=/root/android/mlc-llm/3rdparty/tvm
export MLC_LLM_SOURCE_DIR=/root/android/mlc-llm
mlc_llm convert_weight /root/models/internlm2_5-1_8b-chat/ \
--quantization q4f16_1 \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
```
### 2.3 生成配置
### 2.3 (可选)生成配置
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `gen_config` 生成 `mlc-chat-config.json` 并处理 `tokenizer`

出现提示时输入`y`
Expand All@@ -94,12 +99,16 @@ mlc_llm gen_config /root/models/internlm2_5-1_8b-chat/ \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
Do you wish to run the custom code? [y/N] y
```
### 2.4 上传到huggingface
上传这一步需要能访问huggingface，可能需要部署代理
如果没有代理可以直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
### 2.4 (可选)上传到huggingface
上传这一步需要能访问huggingface，可能需要**部署代理**并耗费一定流量

具体方法可以参考网上的大量教程

如果不想上传到huggingface可以跳过这一步，直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
[https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC](https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC)
### 2.5 (可选) 测试转换的模型
### 2.5 (可选) 测试转换的模型
在打包之前可以测试模型效果，需要编译成二进制文件

在个人电脑上运行测试代码正常，**InternStudio**上**暂未成功**
```

Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

修改环境搭建方法#1758

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Merged
vansin merged 2 commits into from
Aug 22, 2024
Merged

修改环境搭建方法 #1758

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2ee570d
修改环境搭建方法
qew21 Aug 22, 2024
8e12dde
add model link
qew21 Aug 22, 2024
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39 changes: 24 additions & 15 deletions docs/EasterEgg/Android/readme.md
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,7 +29,7 @@ tar -xvzf android-studio-2024.1.1.12-linux.tar.gz
cd android-studio
wget https://dl.google.com/android/repository/commandlinetools-linux-11076708_latest.zip?hl=zh-cn
unzip commandlinetools-linux-11076708_latest.zip\?hl\=zh-cn
export JAVA_HOME=/root/Downloads/android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;android-34" "build-tools;33.0.1" --sdk_root='sdk'
```

Expand All@@ -39,24 +39,22 @@ cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;andr
. "$HOME/.cargo/env"
export ANDROID_NDK=/root/android/android-studio/sdk/ndk/27.0.12077973
export TVM_NDK_CC=$ANDROID_NDK/toolchains/llvm/prebuilt/linux-x86_64/bin/aarch64-linux-android24-clang
export JAVA_HOME=/root/android//android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
export ANDROID_HOME=/root/android/android-studio/sdk
export PATH=/usr/local/cuda-12/bin:$PATH
export PATH=/root/android/android-studio/sdk/cmake/3.22.1/bin:$PATH
```
## 2 转换模型
### 2.1 安装mlc-llm
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)
（如果下载很慢可以取消重新运行一下，或者本地下载了拷过去）
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)，安装`mlc-llm`可能**需要代理**

安装`pytorch`部分也可以使用其他包含`torch`的`conda`环境
```
conda create --name mlc-prebuilt python=3.11
conda activate mlc-prebuilt
conda install -c conda-forge git-lfs
pip install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 transformers sentencepiece protobuf
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
python -m pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightly-cu122 mlc-ai-nightly-cu122
```
测试如下输出说明安装正确

Expand All@@ -72,17 +70,24 @@ cd mlc-llm
git submodule update --init --recursive
```

### 2.2 转换参数
### 2.2 (可选)转换参数
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `convert_weight` 对模型参数进行转换和量化，转换后的参数可以跨平台使用

```
mkdir -p /root/models/
ln -s /share/new_models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat /root/models/internlm2_5-1_8b-chat
cd android/MLCChat
export TVM_SOURCE_DIR=/root/android/mlc-llm/3rdparty/tvm
export MLC_LLM_SOURCE_DIR=/root/android/mlc-llm
mlc_llm convert_weight /root/models/internlm2_5-1_8b-chat/ \
--quantization q4f16_1 \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
```
### 2.3 生成配置
### 2.3 (可选)生成配置
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `gen_config` 生成 `mlc-chat-config.json` 并处理 `tokenizer`

出现提示时输入`y`
Expand All@@ -94,12 +99,16 @@ mlc_llm gen_config /root/models/internlm2_5-1_8b-chat/ \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
Do you wish to run the custom code? [y/N] y
```
### 2.4 上传到huggingface
上传这一步需要能访问huggingface，可能需要部署代理
如果没有代理可以直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
### 2.4 (可选)上传到huggingface
上传这一步需要能访问huggingface，可能需要**部署代理**并耗费一定流量

具体方法可以参考网上的大量教程

如果不想上传到huggingface可以跳过这一步，直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
[https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC](https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC)
### 2.5 (可选) 测试转换的模型
### 2.5 (可选) 测试转换的模型
在打包之前可以测试模型效果，需要编译成二进制文件

在个人电脑上运行测试代码正常，**InternStudio**上**暂未成功**
```

Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length \u003e 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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修改环境搭建方法#1758

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Merged
vansin merged 2 commits into from
Aug 22, 2024
Merged

修改环境搭建方法 #1758

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qew21 Aug 22, 2024
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add model link
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39 changes: 24 additions & 15 deletions docs/EasterEgg/Android/readme.md
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,7 +29,7 @@ tar -xvzf android-studio-2024.1.1.12-linux.tar.gz
cd android-studio
wget https://dl.google.com/android/repository/commandlinetools-linux-11076708_latest.zip?hl=zh-cn
unzip commandlinetools-linux-11076708_latest.zip\?hl\=zh-cn
export JAVA_HOME=/root/Downloads/android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;android-34" "build-tools;33.0.1" --sdk_root='sdk'
```

Expand All@@ -39,24 +39,22 @@ cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;andr
. "$HOME/.cargo/env"
export ANDROID_NDK=/root/android/android-studio/sdk/ndk/27.0.12077973
export TVM_NDK_CC=$ANDROID_NDK/toolchains/llvm/prebuilt/linux-x86_64/bin/aarch64-linux-android24-clang
export JAVA_HOME=/root/android//android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
export ANDROID_HOME=/root/android/android-studio/sdk
export PATH=/usr/local/cuda-12/bin:$PATH
export PATH=/root/android/android-studio/sdk/cmake/3.22.1/bin:$PATH
```
## 2 转换模型
### 2.1 安装mlc-llm
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)
（如果下载很慢可以取消重新运行一下，或者本地下载了拷过去）
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)，安装`mlc-llm`可能**需要代理**

安装`pytorch`部分也可以使用其他包含`torch`的`conda`环境
```
conda create --name mlc-prebuilt python=3.11
conda activate mlc-prebuilt
conda install -c conda-forge git-lfs
pip install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 transformers sentencepiece protobuf
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
python -m pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightly-cu122 mlc-ai-nightly-cu122
```
测试如下输出说明安装正确

Expand All@@ -72,17 +70,24 @@ cd mlc-llm
git submodule update --init --recursive
```

### 2.2 转换参数
### 2.2 (可选)转换参数
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `convert_weight` 对模型参数进行转换和量化，转换后的参数可以跨平台使用

```
mkdir -p /root/models/
ln -s /share/new_models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat /root/models/internlm2_5-1_8b-chat
cd android/MLCChat
export TVM_SOURCE_DIR=/root/android/mlc-llm/3rdparty/tvm
export MLC_LLM_SOURCE_DIR=/root/android/mlc-llm
mlc_llm convert_weight /root/models/internlm2_5-1_8b-chat/ \
--quantization q4f16_1 \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
```
### 2.3 生成配置
### 2.3 (可选)生成配置
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `gen_config` 生成 `mlc-chat-config.json` 并处理 `tokenizer`

出现提示时输入`y`
Expand All@@ -94,12 +99,16 @@ mlc_llm gen_config /root/models/internlm2_5-1_8b-chat/ \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
Do you wish to run the custom code? [y/N] y
```
### 2.4 上传到huggingface
上传这一步需要能访问huggingface，可能需要部署代理
如果没有代理可以直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
### 2.4 (可选)上传到huggingface
上传这一步需要能访问huggingface，可能需要**部署代理**并耗费一定流量

具体方法可以参考网上的大量教程

如果不想上传到huggingface可以跳过这一步，直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
[https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC](https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC)
### 2.5 (可选) 测试转换的模型
### 2.5 (可选) 测试转换的模型
在打包之前可以测试模型效果，需要编译成二进制文件

在个人电脑上运行测试代码正常，**InternStudio**上**暂未成功**
```

Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content

修改环境搭建方法#1758

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Merged
vansin merged 2 commits into from
Aug 22, 2024
Merged

修改环境搭建方法 #1758

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2 commits
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2ee570d
修改环境搭建方法
qew21 Aug 22, 2024
8e12dde
add model link
qew21 Aug 22, 2024
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39 changes: 24 additions & 15 deletions docs/EasterEgg/Android/readme.md
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,7 +29,7 @@ tar -xvzf android-studio-2024.1.1.12-linux.tar.gz
cd android-studio
wget https://dl.google.com/android/repository/commandlinetools-linux-11076708_latest.zip?hl=zh-cn
unzip commandlinetools-linux-11076708_latest.zip\?hl\=zh-cn
export JAVA_HOME=/root/Downloads/android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;android-34" "build-tools;33.0.1" --sdk_root='sdk'
```

Expand All@@ -39,24 +39,22 @@ cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;andr
. "$HOME/.cargo/env"
export ANDROID_NDK=/root/android/android-studio/sdk/ndk/27.0.12077973
export TVM_NDK_CC=$ANDROID_NDK/toolchains/llvm/prebuilt/linux-x86_64/bin/aarch64-linux-android24-clang
export JAVA_HOME=/root/android//android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
export ANDROID_HOME=/root/android/android-studio/sdk
export PATH=/usr/local/cuda-12/bin:$PATH
export PATH=/root/android/android-studio/sdk/cmake/3.22.1/bin:$PATH
```
## 2 转换模型
### 2.1 安装mlc-llm
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)
（如果下载很慢可以取消重新运行一下，或者本地下载了拷过去）
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)，安装`mlc-llm`可能**需要代理**

安装`pytorch`部分也可以使用其他包含`torch`的`conda`环境
```
conda create --name mlc-prebuilt python=3.11
conda activate mlc-prebuilt
conda install -c conda-forge git-lfs
pip install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 transformers sentencepiece protobuf
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
python -m pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightly-cu122 mlc-ai-nightly-cu122
```
测试如下输出说明安装正确

Expand All@@ -72,17 +70,24 @@ cd mlc-llm
git submodule update --init --recursive
```

### 2.2 转换参数
### 2.2 (可选)转换参数
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `convert_weight` 对模型参数进行转换和量化，转换后的参数可以跨平台使用

```
mkdir -p /root/models/
ln -s /share/new_models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat /root/models/internlm2_5-1_8b-chat
cd android/MLCChat
export TVM_SOURCE_DIR=/root/android/mlc-llm/3rdparty/tvm
export MLC_LLM_SOURCE_DIR=/root/android/mlc-llm
mlc_llm convert_weight /root/models/internlm2_5-1_8b-chat/ \
--quantization q4f16_1 \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
```
### 2.3 生成配置
### 2.3 (可选)生成配置
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `gen_config` 生成 `mlc-chat-config.json` 并处理 `tokenizer`

出现提示时输入`y`
Expand All@@ -94,12 +99,16 @@ mlc_llm gen_config /root/models/internlm2_5-1_8b-chat/ \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
Do you wish to run the custom code? [y/N] y
```
### 2.4 上传到huggingface
上传这一步需要能访问huggingface，可能需要部署代理
如果没有代理可以直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
### 2.4 (可选)上传到huggingface
上传这一步需要能访问huggingface，可能需要**部署代理**并耗费一定流量

具体方法可以参考网上的大量教程

如果不想上传到huggingface可以跳过这一步，直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
[https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC](https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC)
### 2.5 (可选) 测试转换的模型
### 2.5 (可选) 测试转换的模型
在打包之前可以测试模型效果，需要编译成二进制文件

在个人电脑上运行测试代码正常，**InternStudio**上**暂未成功**
```

Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

修改环境搭建方法#1758

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Merged
vansin merged 2 commits into from
Aug 22, 2024
Merged

修改环境搭建方法 #1758

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2 commits
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2ee570d
修改环境搭建方法
qew21 Aug 22, 2024
8e12dde
add model link
qew21 Aug 22, 2024
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39 changes: 24 additions & 15 deletions docs/EasterEgg/Android/readme.md
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,7 +29,7 @@ tar -xvzf android-studio-2024.1.1.12-linux.tar.gz
cd android-studio
wget https://dl.google.com/android/repository/commandlinetools-linux-11076708_latest.zip?hl=zh-cn
unzip commandlinetools-linux-11076708_latest.zip\?hl\=zh-cn
export JAVA_HOME=/root/Downloads/android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;android-34" "build-tools;33.0.1" --sdk_root='sdk'
```

Expand All@@ -39,24 +39,22 @@ cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;andr
. "$HOME/.cargo/env"
export ANDROID_NDK=/root/android/android-studio/sdk/ndk/27.0.12077973
export TVM_NDK_CC=$ANDROID_NDK/toolchains/llvm/prebuilt/linux-x86_64/bin/aarch64-linux-android24-clang
export JAVA_HOME=/root/android//android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
export ANDROID_HOME=/root/android/android-studio/sdk
export PATH=/usr/local/cuda-12/bin:$PATH
export PATH=/root/android/android-studio/sdk/cmake/3.22.1/bin:$PATH
```
## 2 转换模型
### 2.1 安装mlc-llm
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)
（如果下载很慢可以取消重新运行一下，或者本地下载了拷过去）
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)，安装`mlc-llm`可能**需要代理**

安装`pytorch`部分也可以使用其他包含`torch`的`conda`环境
```
conda create --name mlc-prebuilt python=3.11
conda activate mlc-prebuilt
conda install -c conda-forge git-lfs
pip install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 transformers sentencepiece protobuf
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
python -m pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightly-cu122 mlc-ai-nightly-cu122
```
测试如下输出说明安装正确

Expand All@@ -72,17 +70,24 @@ cd mlc-llm
git submodule update --init --recursive
```

### 2.2 转换参数
### 2.2 (可选)转换参数
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `convert_weight` 对模型参数进行转换和量化，转换后的参数可以跨平台使用

```
mkdir -p /root/models/
ln -s /share/new_models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat /root/models/internlm2_5-1_8b-chat
cd android/MLCChat
export TVM_SOURCE_DIR=/root/android/mlc-llm/3rdparty/tvm
export MLC_LLM_SOURCE_DIR=/root/android/mlc-llm
mlc_llm convert_weight /root/models/internlm2_5-1_8b-chat/ \
--quantization q4f16_1 \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
```
### 2.3 生成配置
### 2.3 (可选)生成配置
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `gen_config` 生成 `mlc-chat-config.json` 并处理 `tokenizer`

出现提示时输入`y`
Expand All@@ -94,12 +99,16 @@ mlc_llm gen_config /root/models/internlm2_5-1_8b-chat/ \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
Do you wish to run the custom code? [y/N] y
```
### 2.4 上传到huggingface
上传这一步需要能访问huggingface，可能需要部署代理
如果没有代理可以直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
### 2.4 (可选)上传到huggingface
上传这一步需要能访问huggingface，可能需要**部署代理**并耗费一定流量

具体方法可以参考网上的大量教程

如果不想上传到huggingface可以跳过这一步，直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
[https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC](https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC)
### 2.5 (可选) 测试转换的模型
### 2.5 (可选) 测试转换的模型
在打包之前可以测试模型效果，需要编译成二进制文件

在个人电脑上运行测试代码正常，**InternStudio**上**暂未成功**
```

Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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修改环境搭建方法#1758

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Merged
vansin merged 2 commits into from
Aug 22, 2024
Merged

修改环境搭建方法 #1758

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39 changes: 24 additions & 15 deletions docs/EasterEgg/Android/readme.md
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,7 +29,7 @@ tar -xvzf android-studio-2024.1.1.12-linux.tar.gz
cd android-studio
wget https://dl.google.com/android/repository/commandlinetools-linux-11076708_latest.zip?hl=zh-cn
unzip commandlinetools-linux-11076708_latest.zip\?hl\=zh-cn
export JAVA_HOME=/root/Downloads/android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;android-34" "build-tools;33.0.1" --sdk_root='sdk'
```

Expand All@@ -39,24 +39,22 @@ cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;andr
. "$HOME/.cargo/env"
export ANDROID_NDK=/root/android/android-studio/sdk/ndk/27.0.12077973
export TVM_NDK_CC=$ANDROID_NDK/toolchains/llvm/prebuilt/linux-x86_64/bin/aarch64-linux-android24-clang
export JAVA_HOME=/root/android//android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
export ANDROID_HOME=/root/android/android-studio/sdk
export PATH=/usr/local/cuda-12/bin:$PATH
export PATH=/root/android/android-studio/sdk/cmake/3.22.1/bin:$PATH
```
## 2 转换模型
### 2.1 安装mlc-llm
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)
（如果下载很慢可以取消重新运行一下，或者本地下载了拷过去）
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)，安装`mlc-llm`可能**需要代理**

安装`pytorch`部分也可以使用其他包含`torch`的`conda`环境
```
conda create --name mlc-prebuilt python=3.11
conda activate mlc-prebuilt
conda install -c conda-forge git-lfs
pip install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 transformers sentencepiece protobuf
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
python -m pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightly-cu122 mlc-ai-nightly-cu122
```
测试如下输出说明安装正确

Expand All@@ -72,17 +70,24 @@ cd mlc-llm
git submodule update --init --recursive
```

### 2.2 转换参数
### 2.2 (可选)转换参数
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `convert_weight` 对模型参数进行转换和量化，转换后的参数可以跨平台使用

```
mkdir -p /root/models/
ln -s /share/new_models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat /root/models/internlm2_5-1_8b-chat
cd android/MLCChat
export TVM_SOURCE_DIR=/root/android/mlc-llm/3rdparty/tvm
export MLC_LLM_SOURCE_DIR=/root/android/mlc-llm
mlc_llm convert_weight /root/models/internlm2_5-1_8b-chat/ \
--quantization q4f16_1 \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
```
### 2.3 生成配置
### 2.3 (可选)生成配置
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `gen_config` 生成 `mlc-chat-config.json` 并处理 `tokenizer`

出现提示时输入`y`
Expand All@@ -94,12 +99,16 @@ mlc_llm gen_config /root/models/internlm2_5-1_8b-chat/ \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
Do you wish to run the custom code? [y/N] y
```
### 2.4 上传到huggingface
上传这一步需要能访问huggingface，可能需要部署代理
如果没有代理可以直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
### 2.4 (可选)上传到huggingface
上传这一步需要能访问huggingface，可能需要**部署代理**并耗费一定流量

具体方法可以参考网上的大量教程

如果不想上传到huggingface可以跳过这一步，直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
[https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC](https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC)
### 2.5 (可选) 测试转换的模型
### 2.5 (可选) 测试转换的模型
在打包之前可以测试模型效果，需要编译成二进制文件

在个人电脑上运行测试代码正常，**InternStudio**上**暂未成功**
```

Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
Skip to content

修改环境搭建方法#1758

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Merged
vansin merged 2 commits into from
Aug 22, 2024
Merged

修改环境搭建方法 #1758

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2 commits
Select commit Hold shift + click to select a range
2ee570d
修改环境搭建方法
qew21 Aug 22, 2024
8e12dde
add model link
qew21 Aug 22, 2024
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39 changes: 24 additions & 15 deletions docs/EasterEgg/Android/readme.md
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,7 +29,7 @@ tar -xvzf android-studio-2024.1.1.12-linux.tar.gz
cd android-studio
wget https://dl.google.com/android/repository/commandlinetools-linux-11076708_latest.zip?hl=zh-cn
unzip commandlinetools-linux-11076708_latest.zip\?hl\=zh-cn
export JAVA_HOME=/root/Downloads/android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;android-34" "build-tools;33.0.1" --sdk_root='sdk'
```

Expand All@@ -39,24 +39,22 @@ cmdline-tools/bin/sdkmanager "ndk;27.0.12077973" "cmake;3.22.1" "platforms;andr
. "$HOME/.cargo/env"
export ANDROID_NDK=/root/android/android-studio/sdk/ndk/27.0.12077973
export TVM_NDK_CC=$ANDROID_NDK/toolchains/llvm/prebuilt/linux-x86_64/bin/aarch64-linux-android24-clang
export JAVA_HOME=/root/android//android-studio/jbr
export JAVA_HOME=/root/android/android-studio/jbr
export ANDROID_HOME=/root/android/android-studio/sdk
export PATH=/usr/local/cuda-12/bin:$PATH
export PATH=/root/android/android-studio/sdk/cmake/3.22.1/bin:$PATH
```
## 2 转换模型
### 2.1 安装mlc-llm
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)
（如果下载很慢可以取消重新运行一下，或者本地下载了拷过去）
参考[https://llm.mlc.ai/docs/install/mlc_llm.html](https://llm.mlc.ai/docs/install/mlc_llm.html)，安装`mlc-llm`可能**需要代理**

安装`pytorch`部分也可以使用其他包含`torch`的`conda`环境
```
conda create --name mlc-prebuilt python=3.11
conda activate mlc-prebuilt
conda install -c conda-forge git-lfs
pip install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 transformers sentencepiece protobuf
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
wget https://github.com/mlc-ai/package/releases/download/v0.9.dev0/mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_ai_nightly_cu122-0.15.dev404-cp311-cp311-manylinux_2_28_x86_64.whl
pip install mlc_llm_nightly_cu122-0.1.dev1445-cp311-cp311-manylinux_2_28_x86_64.whl
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
python -m pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightly-cu122 mlc-ai-nightly-cu122
```
测试如下输出说明安装正确

Expand All@@ -72,17 +70,24 @@ cd mlc-llm
git submodule update --init --recursive
```

### 2.2 转换参数
### 2.2 (可选)转换参数
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `convert_weight` 对模型参数进行转换和量化，转换后的参数可以跨平台使用

```
mkdir -p /root/models/
ln -s /share/new_models/Shanghai_AI_Laboratory/internlm2_5-1_8b-chat /root/models/internlm2_5-1_8b-chat
cd android/MLCChat
export TVM_SOURCE_DIR=/root/android/mlc-llm/3rdparty/tvm
export MLC_LLM_SOURCE_DIR=/root/android/mlc-llm
mlc_llm convert_weight /root/models/internlm2_5-1_8b-chat/ \
--quantization q4f16_1 \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
```
### 2.3 生成配置
### 2.3 (可选)生成配置
（如果不想上传到huggingface可以跳过这一步，有公开上传的）

使用 `mlc_llm` 的 `gen_config` 生成 `mlc-chat-config.json` 并处理 `tokenizer`

出现提示时输入`y`
Expand All@@ -94,12 +99,16 @@ mlc_llm gen_config /root/models/internlm2_5-1_8b-chat/ \
-o dist/internlm2_5-1_8b-chat-q4f16_1-MLC
Do you wish to run the custom code? [y/N] y
```
### 2.4 上传到huggingface
上传这一步需要能访问huggingface，可能需要部署代理
如果没有代理可以直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
### 2.4 (可选)上传到huggingface
上传这一步需要能访问huggingface，可能需要**部署代理**并耗费一定流量

具体方法可以参考网上的大量教程

如果不想上传到huggingface可以跳过这一步，直接在接下来的配置中使用如下链接的模型（和文档中的转换方法一样）
[https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC](https://huggingface.co/timws/internlm2_5-1_8b-chat-q4f16_1-MLC)
### 2.5 (可选) 测试转换的模型
### 2.5 (可选) 测试转换的模型
在打包之前可以测试模型效果，需要编译成二进制文件

在个人电脑上运行测试代码正常，**InternStudio**上**暂未成功**
```

Expand Down