> For the complete documentation index, see [llms.txt](https://unsloth.ai/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://unsloth.ai/docs/zh/xin/studio/export.md).
# 使用 Unsloth Studio 导出模型
了解如何将你的 safetensor 或 LoRA 模型文件导出为 GGUF 或其他格式。
使用 [Unsloth Studio](/docs/zh/xin/studio.md) 可将模型导出、保存或转换为 GGUF、Safetensors 或 LoRA，用于在 Unsloth、llama.cpp、Ollama、vLLM 等环境中部署、共享或进行本地推理。导出已训练的检查点或转换任何现有模型。
{% stepper %}
{% step %}
### 选择训练运行
首先选择要从中导出的训练运行。每次运行代表一个完整的训练会话，并可能包含多个检查点。
选择运行后，选择要导出的检查点。检查点是在训练过程中创建的模型已保存版本。
{% endstep %}
{% step %}
### 选择检查点
较后期的检查点通常代表最终训练模型，但你可以根据需要导出任意检查点。
{% endstep %}
{% step %}
### 导出方法
根据你的工作流程，你可以导出合并模型、LoRA 适配器权重或用于本地推理的 GGUF 模型。
每种导出方法都会生成不同版本的模型，具体取决于你计划如何运行或共享它。下表说明了每个选项导出的内容。
| 导出类型 | 描述 |
| ---------------- | ---------------------------------------------------------------------- |
| 合并模型 | **16 位模型** 将 LoRA 适配器合并到基础权重中。 |
| 仅 LoRA | 导出 **仅适配器权重**。需要原始基础模型。 |
| GGUF / llama.cpp | 将模型转换为 **GGUF 格式** 用于 Unsloth / llama.cpp **/** Ollama / LM Studio 推理。 |
| {% endstep %} | |
{% step %}
### 导出 / 保存到本地
导出模型时，你可以选择结果文件的保存位置。模型可以直接下载到你的机器，或推送到 Hugging Face Hub 以进行托管和共享。
将导出的模型文件直接保存到你的机器上。此选项适用于在本地运行模型、手动分发文件或与本地推理工具集成。
{% endstep %}
{% step %}
### 推送到 Hub
将导出的模型上传到 Hugging Face Hub。这使你可以从中心仓库托管、共享和部署模型。
发布模型需要 Hugging Face 写入令牌。
{% hint style="success" %}
如果你已经通过 Hugging Face CLI 完成身份验证，则写入令牌可以留空。
{% endhint %}
{% endstep %}
{% endstepper %}
---
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