> For the complete documentation index, see [llms.txt](https://docs.clore.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.clore.ai/guides/guides_v2-zh/xun-lian/training.md).

# 概览

在 CLORE.AI GPU 上训练和微调 AI 模型。

## 可用指南

| 指南                                                                       | 使用场景             | 难度 |
| ------------------------------------------------------------------------ | ---------------- | -- |
| [Jupyter 机器学习训练](/guides/guides_v2-zh/xun-lian/jupyter-ml-training.md)   | 交互式训练            | 简单 |
| [DreamBooth](/guides/guides_v2-zh/xun-lian/dreambooth.md)                | 自定义 SD 主题        | 中等 |
| [Kohya 训练](/guides/guides_v2-zh/xun-lian/kohya-training.md)              | LoRA/LyCORIS 训练  | 中等 |
| [微调 LLM](/guides/guides_v2-zh/xun-lian/finetune-llm.md)                  | LLM 微调           | 高级 |
| [DeepSpeed](/guides/guides_v2-zh/xun-lian/deepspeed-training.md)         | 分布式训练            | 高级 |
| [HuggingFace](/guides/guides_v2-zh/xun-lian/huggingface-transformers.md) | Transformers 训练  | 中等 |
| [Unsloth](/guides/guides_v2-zh/xun-lian/unsloth-finetune.md)             | 快速 LLM 微调        | 中等 |
| [Axolotl](/guides/guides_v2-zh/xun-lian/axolotl-training.md)             | 以 YAML 为先的微调     | 中等 |
| [LLaMA-Factory](/guides/guides_v2-zh/xun-lian/llama-factory.md)          | 简易 LLM 训练界面      | 简单 |
| [TRL](/guides/guides_v2-zh/xun-lian/trl.md)                              | Transformer 强化学习 | 高级 |
| [LitGPT](/guides/guides_v2-zh/xun-lian/litgpt.md)                        | 基于 Lightning 的训练 | 中等 |
| [Mergekit](/guides/guides_v2-zh/xun-lian/mergekit.md)                    | 模型合并工具包          | 简单 |

## GPU 推荐

{% hint style="warning" %}
**Clore.ai 市场上未列出多 GPU 的 80GB 级机型。** 目前列出的最大配置是 4× RTX PRO 6000 Blackwell（每张 96GB，共 380GB）以及 8–11× RTX 5090（每张 32GB）。A100 / H200 / B200 容量可按 [裸机](https://clore.ai/bare-metal) 需求提供。部署前请查看 [GPU 价格与可用性](/guides/guides_v2-zh/ru-men-zhi-nan/pricing.md) 。
{% endhint %}

| 任务          | 最低       | 推荐        |
| ----------- | -------- | --------- |
| LoRA（SD）    | RTX 3060 | RTX 3090  |
| DreamBooth  | RTX 3090 | RTX 4090  |
| LLM 微调（7B）  | RTX 3090 | A100 40GB |
| LLM 微调（70B） | 4 张 A100 | 8 张 A100  |

## 训练类型

### 图像模型

* **LoRA** - 轻量级适配器，训练快速
* **DreamBooth** - 用于概念的全量微调
* **文本反演** - 学习新 token

### 语言模型

* **LoRA/QLoRA** - 内存高效微调
* **全量微调** - 质量最佳，但需要更多显存

## 提示

* 使用 **竞价** 长时间训练运行的订单
* 启用梯度检查点以节省显存
* 使用 TensorBoard 监控训练
* 经常保存检查点

## 相关指南

* [语言模型](/guides/guides_v2-zh/yu-yan-mo-xing/language-models.md)
* [图像生成](/guides/guides_v2-zh/tu-xiang-sheng-cheng/image-generation.md)


---

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