add a new notebook

LLM-tutorial/P.训练.ipynb

@@ -0,0 +1,346 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4d252bab-f488-489f-a3a3-a8869cf99dcb",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "1. 安装最新版本的modelscope和swift"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68bbc6b0-e4e5-4663-a28e-fec1e667427b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!pip install modelscope ms-swift -U\n",
+    "!pip install tf-keras==2.16.0 --no-dependencies"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6bc13d59-415b-4455-a965-49cead0904f7",
+   "metadata": {},
+   "source": [
+    "2. 加载数据集"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "9a292aab-04d2-4b68-8507-53f1ea22bb9f",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-11-01T08:24:57.831096Z",
+     "iopub.status.busy": "2024-11-01T08:24:57.830826Z",
+     "iopub.status.idle": "2024-11-01T08:25:07.688996Z",
+     "shell.execute_reply": "2024-11-01T08:25:07.688492Z",
+     "shell.execute_reply.started": "2024-11-01T08:24:57.831080Z"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from modelscope import MsDataset\n",
+    "dataset = MsDataset.load('swift/classical_chinese_translate')\n",
+    "dataset = dataset['train']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fe841e73-3f85-4a4d-879c-0b9064fe9e98",
+   "metadata": {},
+   "source": [
+    "3. 查看数据集内容"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "817f4c82-cf51-4504-8866-09eff41fe732",
+   "metadata": {
+    "ExecutionIndicator": {
+     "show": true
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "print(dataset)\n",
+    "print(dataset['conversations'][0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ac948dfd-f290-43c4-bf4f-7ece4883ccad",
+   "metadata": {},
+   "source": [
+    "4. 加载模型、分词器、模板"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "231ff476-df34-470b-8b73-4bd24e2f298a",
+   "metadata": {
+    "ExecutionIndicator": {
+     "show": true
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "from modelscope import AutoModelForCausalLM\n",
+    "from modelscope import AutoTokenizer\n",
+    "from swift.llm import get_template, TemplateType\n",
+    "tokenizer = AutoTokenizer.from_pretrained('Qwen/Qwen2.5-7B-Instruct', trust_remote_code=True)\n",
+    "model = AutoModelForCausalLM.from_pretrained('Qwen/Qwen2.5-7B-Instruct', torch_dtype=torch.bfloat16, device_map='auto', trust_remote_code=True)\n",
+    "print(model)\n",
+    "print(tokenizer('I like AI'))\n",
+    "\n",
+    "\n",
+    "template = get_template(TemplateType.qwen2_5, tokenizer, max_length=400)\n",
+    "ret = template.encode({'query': 'what is your hobby?', 'response': 'I like AI'})\n",
+    "print(ret)\n",
+    "tokenizer.decode(ret[0]['input_ids'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4dd66f8b-921c-4433-be8d-122bc182920c",
+   "metadata": {},
+   "source": [
+    "5. 预处理数据集"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f41eebe2-7009-41cf-a936-5d4b471daba4",
+   "metadata": {
+    "ExecutionIndicator": {
+     "show": true
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from swift.llm.utils.preprocess import ConversationsPreprocessor\n",
+    "ds = ConversationsPreprocessor()(dataset)\n",
+    "print(ds[0])\n",
+    "\n",
+    "def encode(example):\n",
+    "    example, kwargs = template.encode(example)\n",
+    "    if 'input_ids' not in example:\n",
+    "        return {\n",
+    "            'input_ids': None,\n",
+    "            'labels': None,\n",
+    "        }\n",
+    "    return example\n",
+    "\n",
+    "ds = ds.select(range(300)).map(encode).filter(lambda e: e.get('input_ids'))\n",
+    "ds = ds.train_test_split(test_size=0.1)\n",
+    "\n",
+    "train_dataset, val_dataset = ds['train'], ds['test']\n",
+    "print('===========================================')\n",
+    "print(train_dataset[0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8eb90b4e-7e65-48d7-9f62-d9b226918618",
+   "metadata": {},
+   "source": [
+    "6. 加载LoRA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "9cf58c93-a3e6-4672-80d9-06acc25bd9e8",
+   "metadata": {
+    "ExecutionIndicator": {
+     "show": true
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-01T08:25:51.704754Z",
+     "iopub.status.busy": "2024-11-01T08:25:51.704328Z",
+     "iopub.status.idle": "2024-11-01T08:25:52.427483Z",
+     "shell.execute_reply": "2024-11-01T08:25:52.426958Z",
+     "shell.execute_reply.started": "2024-11-01T08:25:51.704723Z"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from swift import Swift, LoraConfig\n",
+    "\n",
+    "\n",
+    "lora_config = LoraConfig(\n",
+    "                r=8,\n",
+    "                target_modules=['q_proj', 'k_proj', 'v_proj', 'o_proj', 'gate_proj', 'up_proj', 'down_proj'],\n",
+    "                lora_alpha=32,\n",
+    "                lora_dropout=0.05)\n",
+    "model = Swift.prepare_model(model, lora_config)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3a06c9e0-24ff-49a7-b901-54d800248407",
+   "metadata": {},
+   "source": [
+    "7. 训练"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "add78662-d30f-48b7-af7c-358840af1433",
+   "metadata": {
+    "ExecutionIndicator": {
+     "show": true
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# A100 18G memory\n",
+    "from swift import Seq2SeqTrainer, Seq2SeqTrainingArguments\n",
+    "import torch\n",
+    "\n",
+    "\n",
+    "train_args = Seq2SeqTrainingArguments(\n",
+    "    output_dir='output',\n",
+    "    learning_rate=1e-4,\n",
+    "    num_train_epochs=1,\n",
+    "    eval_steps=5,\n",
+    "    save_steps=5,\n",
+    "    evaluation_strategy='no',\n",
+    "    save_strategy='steps',\n",
+    "    dataloader_num_workers=4,\n",
+    "    per_device_train_batch_size=1,\n",
+    "    gradient_accumulation_steps=16,\n",
+    "    logging_steps=2,\n",
+    ")\n",
+    "\n",
+    "print(train_dataset[0])\n",
+    "\n",
+    "trainer = Seq2SeqTrainer(\n",
+    "    model=model,\n",
+    "    args=train_args,\n",
+    "    data_collator=template.data_collator,\n",
+    "    train_dataset=train_dataset,\n",
+    "    eval_dataset=val_dataset,\n",
+    "    tokenizer=tokenizer)\n",
+    "\n",
+    "trainer.train()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "741ed1fd-1623-4221-a7c3-efdd37bc57da",
+   "metadata": {},
+   "source": [
+    "8. 看看存了什么"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7e1a5e23-632d-4487-8a5c-fcae84311f51",
+   "metadata": {
+    "ExecutionIndicator": {
+     "show": true
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!ls output/checkpoint-11"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "799089b3-5458-4b54-9865-131fca081b26",
+   "metadata": {},
+   "source": [
+    "9. 推理"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "00f72b82-e856-48cd-9be5-38afee347b48",
+   "metadata": {
+    "ExecutionIndicator": {
+     "show": true
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from modelscope import GenerationConfig\n",
+    "query = '你喜欢什么'\n",
+    "inputs, kwargs = template.encode({'query': query})\n",
+    "print(inputs)\n",
+    "generation_config = GenerationConfig(max_new_tokens=512, top_p=0.7, temperature=0.3)\n",
+    "inputs['input_ids'] = torch.tensor(inputs['input_ids'])[None].cuda()\n",
+    "generate_ids = model.generate(generation_config=generation_config, **inputs)\n",
+    "print(generate_ids)\n",
+    "print(tokenizer.decode(generate_ids[0]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "95f72cea-a972-4e0c-aad4-4a6f1a5aca25",
+   "metadata": {},
+   "source": [
+    "10. 界面"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bbf4c631-6d3f-4813-8380-96fbf632dac9",
+   "metadata": {
+    "ExecutionIndicator": {
+     "show": true
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!pip install gradio==3.50.2\n",
+    "!swift web-ui"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

README.md

@@ -7,6 +7,7 @@
 在这里我们集中了魔搭社区的深度学习教程！热爱AI的开发者们可以在这里找到自己想要了解的知识，并学会训练、推理、部署、应用搭建等各类常用操作！
 
 # 🌿更新日志
+- ⭐️2024.11.01 补充了一个通用训练流程的notebook，请查看[古文翻译训练样例](./LLM-tutorial/P.训练.ipynb).
 - ⭐️2024.10.30 补充了全流程数据集训练的notebook，请查看[全流程知乎数据集训练](./LLM-tutorial/全流程知乎数据集训练.ipynb).
 - ⭐️2024.10.22 添加了有关 OpenAI-O1 的技术调研，请查看[LLM-tutorial](./LLM-tutorial/从%20OpenAI-O1%20看大模型的复杂推理能力.md).
 - ⭐️2024.06.14 补充了人类偏好对齐训练技术解析，请查看[LLM-tutorial](./LLM-tutorial/M.人类偏好对齐训练.md).

README_EN.md

@@ -5,6 +5,7 @@
 Here we have gathered the deep learning tutorials from the MoDao community! Developers who love AI can find the knowledge they want to learn here, and learn how to train, infer, deploy, build applications, and perform various other common operations!
 
 # 🌿 Update Log
+- ⭐️2024.11.01 Add a common training notebook，请查看[LLM-tutorial](./LLM-tutorial/P.训练.ipynb).
 - ⭐️2024.10.30 Add Zhihu dataset training and evaluating notebook, please check [LLM-tutorial](./LLM-tutorial/全流程知乎数据集训练.ipynb).
 - ⭐️2024.10.22 Add an investigation of O1 preview, check [LLM-tutorial](./LLM-tutorial/从%20OpenAI-O1%20看大模型的复杂推理能力.md).
 - ⭐️2024.06.14 Add human preference alignment training technical analysis, check:[LLM-tutorial](./LLM-tutorial/M.人类偏好对齐训练.md).