From 641ac3581c543c2e94eee6a0e466e636ae0af037 Mon Sep 17 00:00:00 2001 From: Shanshan Shen <467638484@qq.com> Date: Wed, 16 Oct 2024 17:16:28 +0800 Subject: [PATCH] add sentence-transformers and trl docs (#52) --- _static/images/trl.png | Bin 0 -> 485183 bytes index.rst | 38 ++++++++++++++ sources/sentence_transformers/index.rst | 8 +++ sources/sentence_transformers/install.rst | 30 +++++++++++ sources/sentence_transformers/quick_start.rst | 46 ++++++++++++++++ sources/trl/images/image.png | Bin 0 -> 202358 bytes sources/trl/index.rst | 8 +++ sources/trl/install.rst | 38 ++++++++++++++ sources/trl/quick_start.rst | 49 ++++++++++++++++++ 9 files changed, 217 insertions(+) create mode 100644 _static/images/trl.png create mode 100644 sources/sentence_transformers/index.rst create mode 100644 sources/sentence_transformers/install.rst create mode 100644 sources/sentence_transformers/quick_start.rst create mode 100644 sources/trl/images/image.png create mode 100644 sources/trl/index.rst 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+
+
+
+

Sentence Transformers

+

适用于文本和图像的高性能Embedding库

+
+
+
+ +
+ +
+
+
+
+

Transformer Reinforcement Learning

+

适用于SFT、PPO、DPO等方法的模型后训练库

+
+
+
+ +
diff --git a/sources/sentence_transformers/index.rst b/sources/sentence_transformers/index.rst new file mode 100644 index 0000000..c96404b --- /dev/null +++ b/sources/sentence_transformers/index.rst @@ -0,0 +1,8 @@ +Sentence Transformers +============================= + +.. toctree:: + :maxdepth: 2 + + install.rst + quick_start.rst diff --git a/sources/sentence_transformers/install.rst b/sources/sentence_transformers/install.rst new file mode 100644 index 0000000..1f521fc --- /dev/null +++ b/sources/sentence_transformers/install.rst @@ -0,0 +1,30 @@ +安装指南 +=============== + +本教程面向使用 sentence-transformers & 昇腾的开发者,帮助完成昇腾环境下 sentence-transformers 的安装。 + +昇腾环境安装 +--------------- + +请根据已有昇腾产品型号及 CPU 架构等按照 :doc:`快速安装昇腾环境指引 <../ascend/quick_install>` 进行昇腾环境安装。 + +.. warning:: + CANN 最低版本为 8.0.rc1,安装 CANN 时,请同时安装 Kernel 算子包。 + +sentence-transformers 下载安装 +--------------------------------------------------- + +1. 安装项目所需依赖 + +.. code-block:: shell + + pip install sentence-transformers -i https://pypi.tuna.tsinghua.edu.cn/simple + +2. 安装 torch_npu + +.. code-block:: shell + + pip install torch==2.1.0 torch_npu==2.1.0.post6 -i https://pypi.tuna.tsinghua.edu.cn/simple + +.. hint:: + torch_npu 的版本需要匹配 torch 的版本,详细信息请参考:`Ascend Extension for PyTorch `_。 diff --git a/sources/sentence_transformers/quick_start.rst b/sources/sentence_transformers/quick_start.rst new file mode 100644 index 0000000..366007f --- /dev/null +++ b/sources/sentence_transformers/quick_start.rst @@ -0,0 +1,46 @@ +快速开始 +=============== + +.. note:: + + 阅读本篇前,请确保已按照 :doc:`安装教程 <./install>` 准备好昇腾环境及 sentence-transformers ! + +本教程以 `all-MiniLM-L6-v2` 模型为例,讲述如何使用 sentence-transformers 在昇腾 NPU 上实现文本数据的 Embedding。 + +前置准备 +--------------- + +本篇样例代码为 sentence-transformers 的官方样例,需提前进行下载: + +.. code-block:: + + git clone https://github.com/UKPLab/sentence-transformers.git + +使用模型 +--------------- + +进入 sentence-transformers 项目目录,依次执行如下命令: + +.. code-block:: + + cd examples/applications/computing-embeddings + python computing_embeddings.py + +出现如下日志则代表执行成功: + +:: + + 2024-10-15 08:11:36 - Use pytorch device_name: npu + 2024-10-15 08:11:36 - Load pretrained SentenceTransformer: all-MiniLM-L6-v2 + [W compiler_depend.ts:623] Warning: expandable_segments currently defaults to false. You can enable this feature by `export PYTORCH_NPU_ALLOC_CONF = expandable_segments:True`. (function operator()) + Batches: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1.61it/s] + Sentence: This framework generates embeddings for each input sentence + Embedding: [-0.01375547 -0.04301599 -0.01562478 ... 0.10029524 0.12379668 -0.04230832] + + Sentence: Sentences are passed as a list of string. + Embedding: [ 0.05640831 0.05488579 0.03137118 ... 0.06652435 0.08493122 -0.03337045] + + Sentence: The quick brown fox jumps over the lazy dog. + Embedding: [0.04393559 0.05903088 0.04824848 ... 0.05215353 0.05615513 0.10205095] + +可以看到该模型成功生成了这些句子对应的 Embedding 向量。 diff --git a/sources/trl/images/image.png b/sources/trl/images/image.png new file mode 100644 index 0000000000000000000000000000000000000000..bf674bed61061383c36c7427013d7e9ec974f523 GIT binary patch literal 202358 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+=================================================== + +.. toctree:: + :maxdepth: 2 + + install.rst + quick_start.rst diff --git a/sources/trl/install.rst b/sources/trl/install.rst new file mode 100644 index 0000000..f1c74e9 --- /dev/null +++ b/sources/trl/install.rst @@ -0,0 +1,38 @@ +安装指南 +=============== + +本教程面向使用 TRL (Transformer Reinforcement Learning) & 昇腾的开发者,帮助完成昇腾环境下 TRL 的安装。 + +昇腾环境安装 +--------------- + +请根据已有昇腾产品型号及 CPU 架构等按照 :doc:`快速安装昇腾环境指引 <../ascend/quick_install>` 进行昇腾环境安装。 + +.. warning:: + CANN 最低版本为 8.0.rc1,安装 CANN 时,请同时安装 Kernel 算子包。 + +TRL 下载安装 +--------------- + +1. 安装项目所需依赖 + +.. code-block:: shell + + pip install trl -i https://pypi.tuna.tsinghua.edu.cn/simple + +另外,本项目需要手动安装 transformers 仓库的最新 main 分支,否则可能会出现如下错误: + +.. image:: ./images/image.png + +.. code-block:: shell + + pip install git+https://github.com/huggingface/transformers.git + +2. 安装 torch_npu + +.. code-block:: shell + + pip install torch==2.1.0 torch_npu==2.1.0.post6 -i https://pypi.tuna.tsinghua.edu.cn/simple + +.. hint:: + torch_npu 的版本需要匹配 torch 的版本,详细信息请参考:`Ascend Extension for PyTorch `_。 diff --git a/sources/trl/quick_start.rst b/sources/trl/quick_start.rst new file mode 100644 index 0000000..987b5b0 --- /dev/null +++ b/sources/trl/quick_start.rst @@ -0,0 +1,49 @@ +快速开始 +=============== + +.. note:: + + 阅读本篇前,请确保已按照 :doc:`安装教程 <./install>` 准备好昇腾环境及 TRL (Transformer Reinforcement Learning) ! + +本教程以 DPO 方法为例,讲述如何使用 TRL 在昇腾 NPU 上进行模型的后训练。 + +前置准备 +--------------- + +本篇样例代码为 TRL 官方样例,需提前进行下载: + +.. code-block:: + + git clone https://github.com/huggingface/trl.git + +模型训练 +--------------- + +进入 TRL 项目目录,依次执行如下命令: + +.. code-block:: + + cd examples/scripts + python dpo.py + +出现如下日志则代表训练成功: + +:: + + Tokenizing train dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 62135/62135 [07:11<00:00, 143.85 examples/s] + Tokenizing eval dataset: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 144.73 examples/s] + Detected kernel version 4.19.90, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher. + 0%| ... | 0/3883 [00:00