Ollama模型迁移

技术背景

在前面的一些文章中，我们介绍过使用Ollama在Linux平台加载DeepSeek蒸馏模型，使用Ollama在Windows平台部署DeepSeek本地模型。除了使用Ollama与模型文件交互，还可以使用llama.cpp和KTransformer这样的。也有一些ChatBox、AnythingLLM和PageAssist这样的客户端工具推荐。

这里我们考虑到这样的一个使用场景，在我们使用ollama pull或者是从ModelScope、Hugging Face等平台下载好了一个本地模型之后，例如已经加载到Ollama里面，那么如何把这个模型导出到其他硬件里面去呢？

Ollama模型路径

如果没有去手动配置Ollama的Model路径，在Linux上默认的Ollama模型路径为：

/usr/share/ollama/.ollama/models/

是一个需要root权限的文件夹。在Windows平台上这个路径一般是：

C:\Users\user_name\.ollama\models

Ollama路径含义

在models这个路径下有两个子目录：

drwxr-xr-x 2 ollama ollama 4096 2月  20 14:47 blobs/
drwxr-xr-x 3 ollama ollama 4096 2月  20 14:53 manifests/

其中blobs里面存放的是一系列的模型文件，以sha256开头，后面跟一长串的哈希值：

$ ll blobs/
总用量 106751780
drwxr-xr-x 2 ollama ollama        4096 2月  20 14:47 ./
drwxr-xr-x 4 ollama ollama        4096 2月   5 12:24 ../
-rw-r--r-- 1 ollama ollama         412 2月  14 15:43 sha256-066df13e4debff21aeb0bb1ce8db63b9f19498d06b477ba3a4fa066adafd2949
-rwxr-xr-x 1 root   root          7712 2月  20 14:46 sha256-0b4284c1f87029e67654c7953afa16279961632cf73dcfe33374c4c2f298fa35
-rwxr-xr-x 1 root   root    5963057248 2月  20 14:46 sha256-11f274007f093fefeec994a5dbbb33d0733a4feb87f7ab66dcd7c1069fef0068

这些文件其实就是模型的GGUF文件，可以直接cp为gguf的后缀来使用。但关键的是有时候一个模型可能对应多个GGUF文件，所以需要一个索引文件。manifests目录存放的是每个模型的索引：

$ tree manifests/
manifests/
└── registry.ollama.ai
    └── library
        ├── deepseek-r1
        │   ├── 14b
        │   ├── 32b
        │   ├── 32b-q2k
        │   ├── 32b-q40
        │   └── 70b-q2k
        ├── llama3-vision
        │   └── 11b
        └── nomic-embed-text-v1.5
            └── latest

5 directories, 7 files

这就是Ollama模型存储的一个基本结构。

查找对应模型文件

其实在上一个章节的这个索引文件里面就明文包含了模型文件的对照路径，例如打开一个llama3的索引文件：

{"schemaVersion":2,"mediaType":"application/vnd.docker.distribution.manifest.v2+json","config":{"mediaType":"application/vnd.docker.container.image.v1+json","digest":"sha256:fbd313562bb706ac00f1a18c0aad8398b3c22d5cd78c47ff6f7246c4c3438576","size":572},"layers":[{"mediaType":"application/vnd.ollama.image.model","digest":"sha256:11f274007f093fefeec994a5dbbb33d0733a4feb87f7ab66dcd7c1069fef0068","size":5963057248},{"mediaType":"application/vnd.ollama.image.projector","digest":"sha256:ece5e659647a20a5c28ab9eea1c12a1ad430bc0f2a27021d00ad103b3bf5206f","size":1938763584,"from":"/Users/ollama/.ollama/models/blobs/sha256-ece5e659647a20a5c28ab9eea1c12a1ad430bc0f2a27021d00ad103b3bf5206f"},{"mediaType":"application/vnd.ollama.image.template","digest":"sha256:715415638c9c4c0cb2b78783da041b97bd1205f8b9f9494bd7e5a850cb443602","size":269},{"mediaType":"application/vnd.ollama.image.license","digest":"sha256:0b4284c1f87029e67654c7953afa16279961632cf73dcfe33374c4c2f298fa35","size":7712},{"mediaType":"application/vnd.ollama.image.params","digest":"sha256:fefc914e46e6024467471837a48a24251db2c6f3f58395943da7bf9dc6f70fb6","size":32}]}

这里面带sha256的，都是模型所需要用到的gguf文件。相比于这种直接打开索引文件来检索的方法，Ollama其实还有一种更加优雅的查看模型存储地址的方法：

$ ollama show --modelfile llama3-vision:11b
# Modelfile generated by "ollama show"
# To build a new Modelfile based on this, replace FROM with:
# FROM llama3-vision:11b

FROM /usr/share/ollama/.ollama/models/blobs/sha256-11f274007f093fefeec994a5dbbb33d0733a4feb87f7ab66dcd7c1069fef0068
FROM /usr/share/ollama/.ollama/models/blobs/sha256-ece5e659647a20a5c28ab9eea1c12a1ad430bc0f2a27021d00ad103b3bf5206f
TEMPLATE """{{- range $index, $_ := .Messages }}<|start_header_id|>{{ .Role }}<|end_header_id|>

{{ .Content }}
{{- if gt (len (slice $.Messages $index)) 1 }}<|eot_id|>
{{- else if ne .Role "assistant" }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

{{ end }}
{{- end }}"""
PARAMETER temperature 0.6
PARAMETER top_p 0.9
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使用这个show指令也能够查看到模型存储地址，除了模型地址之外，还有整个的LICENSE。但是这里我们也发现了一个非常重要的问题：通过ollama show列举出来的GGUF模型文件不全！！！。因此，还是建议直接打开manifests中的配置文件进行查看，再迁移相关的模型文件。

模型迁移和加载

在前面了解清楚Ollama的模型文件的存储结构之后，我们要迁移模型，思路就很清晰了：直接把模型文件和索引文件拷贝到相应的路径下就可以了。例如，把sha256的gguf文件拷贝目标设备的blobs路径下，再按照manifests的目录结构，把索引文件拷贝到manifests的路径下。其中如果是Linux操作系统，如下结构是固定的：

manifests/
└── registry.ollama.ai
    └── library

然后在library下创建一个模型名称命名的目录，例如model-name/，然后把配置文件config拷贝到这个路径下，那么加载模型的时候需要使用的指令就是：

$ ollama run model-name:config

需要注意的是，刚把模型迁移过来的时候，直接使用PageAssist等工具可能找不到本地刚迁移过来的模型，需要先ollama run一次，才能够在模型列表里面找到：

$ ollama list
NAME                            ID              SIZE      MODIFIED          
llama3-vision:11b               085a1fdae525    7.9 GB    About an hour ago

到这里，Ollama的模型迁移就完成了。

总结概要

为了方便本地大模型部署和迁移，本文提供了一个关于Ollama的模型本地迁移的方法。由于直接从Ollama Hub下载下来的模型，或者是比较大的GGUF模型文件，往往会被切分成多个，而文件名在Ollama的路径中又被执行了sha256散列变换。因此我们需要从索引文件中获取相应的文件名，再进行模型本地迁移。

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