4、Ollama API - Powered by MinDoc

Ollama 快速入门：Ollama API

Ollama 提供了功能丰富的应用程序接口，它允许我们与 AI 模型进行交互和管理。充分的了解 Ollama API 对我们了解 Ollama 的使用很有必要。

公约

型号名称

模型名称遵循以下model:tag格式：其中model可以有一个可选的命名空间，例如example/model。一些示例是orca-mini:3b-q4_1和llama3:70b。标签是可选的，如果未提供，则默认为latest。标签用于标识特定版本。

持续时间

所有持续时间均以纳秒为单位返回。

流式响应

某些端点将响应流式传输为 JSON 对象。可以通过提供{"stream": false}这些端点来禁用流式传输。

生成文本（Generate a completion）

POST /api/generate

使用提供的模型针对给定的提示生成响应。这是一个流式端点，因此会有一系列响应。最终的响应对象将包括来自请求的统计信息和其他数据。

参数

model: (必须) 模型名称
prompt: 生成响应的 prompt
images: (可选) base64 编码图像列表 (用于多模态模型，例如 llava)

高级参数（可选）：

format: 响应返回的格式。目前唯一接受的值是 json
options: Modelfile 文档中列出的其他模型参数，例如 temperature
system: 系统消息（覆盖 Modelfile中定义的内容）
template: 要使用的提示模板（覆盖 Modelfile 中定义的内容）
context: 从上一次请求返回的上下文参数 /generate，可用于保存简短的对话记忆
stream: 如果 false 响应将作为单个响应对象返回，而不是对象流
raw: 如果 true 提示不应用任何格式. 如果您在向 API 发出的请求中指定了完整的模板提示，可以选择使用 raw 参数
keep_alive: 控制模型在请求后保持加载到内存中的时间 (默认: 5m)

JSON 模式

通过将 format 参数设置为 json 来启用 JSON 模式. 这会将响应构造为有效的 JSON 对象。请参阅下面的 JSON 模式示例。

注意：指示模型在 prompt 中使用 JSON 非常重要。否则，模型可能会产生大量空白。

示例

Generate 请求 (Streaming)

请求

curl http://localhost:11434/api/generate -d '{
  "model": "llama3",
  "prompt": "Why is the sky blue?"
}'

响应

返回JSON对象流：

{
  "model": "llama3",
  "created_at": "2023-08-04T08:52:19.385406455-07:00",
  "response": "The",
  "done": false
}

最终响应流中还包括有关生成的其他数据：

total_duration: 生成响应所花费的时间
load_duration: 加载模型所花费的时间（以纳秒为单位）
prompt_eval_count: prompt 中的标记数
prompt_eval_duration: 执行 prompt 所花费的时间（以纳秒为单位）
eval_count: 响应中的tokens 数
eval_duration: 生成响应所用的时间（以纳秒为单位）
context: 此响应中使用的对话编码，可在下一个请求中发送以保留对话记忆
response: 如果响应是流式传输的，则为空；如果响应不是流式传输的，则将包含完整响应

要计算每秒生成令牌数 (token/s) 的响应速度， eval_count / eval_duration * 10^9。

{
  "model": "llama3",
  "created_at": "2023-08-04T19:22:45.499127Z",
  "response": "",
  "done": true,
  "context": [1, 2, 3],
  "total_duration": 10706818083,
  "load_duration": 6338219291,
  "prompt_eval_count": 26,
  "prompt_eval_duration": 130079000,
  "eval_count": 259,
  "eval_duration": 4232710000
}

Generate 请求 (No streaming)

Request

当流关闭时，一次回复即可收到响应。

curl http://localhost:11434/api/generate -d '{
  "model": "llama3",
  "prompt": "Why is the sky blue?",
  "stream": false
}'

Response

如果 stream 设置为 false, 响应将是单个 JSON 对象：

{
  "model": "llama3",
  "created_at": "2023-08-04T19:22:45.499127Z",
  "response": "The sky is blue because it is the color of the sky.",
  "done": true,
  "context": [1, 2, 3],
  "total_duration": 5043500667,
  "load_duration": 5025959,
  "prompt_eval_count": 26,
  "prompt_eval_duration": 325953000,
  "eval_count": 290,
  "eval_duration": 4709213000
}

请求 (JSON mode)

当 format 设置为时 json, 输出将始终是格式正确的 JSON 对象。指示模型以 JSON 格式响应也很重要。

Request

curl http://localhost:11434/api/generate -d '{
  "model": "llama3",
  "prompt": "What color is the sky at different times of the day? Respond using JSON",
  "format": "json",
  "stream": false
}'

Response

{
  "model": "llama3",
  "created_at": "2023-11-09T21:07:55.186497Z",
  "response": "{\n\"morning\": {\n\"color\": \"blue\"\n},\n\"noon\": {\n\"color\": \"blue-gray\"\n},\n\"afternoon\": {\n\"color\": \"warm gray\"\n},\n\"evening\": {\n\"color\": \"orange\"\n}\n}\n",
  "done": true,
  "context": [1, 2, 3],
  "total_duration": 4648158584,
  "load_duration": 4071084,
  "prompt_eval_count": 36,
  "prompt_eval_duration": 439038000,
  "eval_count": 180,
  "eval_duration": 4196918000
}

response 的值将是一个包含类似以下内容的 JSON 的字符串:

{
  "morning": {
    "color": "blue"
  },
  "noon": {
    "color": "blue-gray"
  },
  "afternoon": {
    "color": "warm gray"
  },
  "evening": {
    "color": "orange"
  }
}

Request (with images)

要将图像提交到多模态模型，（如：llava 或 bakllava），请提供 base64 编码的 images 列表:

Request

curl http://localhost:11434/api/generate -d '{
  "model": "llava",
  "prompt":"What is in this picture?",
  "stream": false,
  "images": ["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"]
}'

Response

{
  "model": "llava",
  "created_at": "2023-11-03T15:36:02.583064Z",
  "response": "A happy cartoon character, which is cute and cheerful.",
  "done": true,
  "context": [1, 2, 3],
  "total_duration": 2938432250,
  "load_duration": 2559292,
  "prompt_eval_count": 1,
  "prompt_eval_duration": 2195557000,
  "eval_count": 44,
  "eval_duration": 736432000
}

Request (Raw Mode)

在某些情况下，您可能希望绕过系统模板并提供完整提示。在这种情况下，您可以使用参数 raw 来禁用模板。另请注意，原始模式不会返回上下文。

Request

curl http://localhost:11434/api/generate -d '{
  "model": "mistral",
  "prompt": "[INST] why is the sky blue? [/INST]",
  "raw": true,
  "stream": false
}'

Request (Reproducible outputs)

对于可重现的输出，设置seed 为一个固定数字：

Request

curl http://localhost:11434/api/generate -d '{
  "model": "mistral",
  "prompt": "Why is the sky blue?",
  "options": {
    "seed": 123
  }
}'

Response

{
  "model": "mistral",
  "created_at": "2023-11-03T15:36:02.583064Z",
  "response": " The sky appears blue because of a phenomenon called Rayleigh scattering.",
  "done": true,
  "total_duration": 8493852375,
  "load_duration": 6589624375,
  "prompt_eval_count": 14,
  "prompt_eval_duration": 119039000,
  "eval_count": 110,
  "eval_duration": 1779061000
}

Generate 请求 (With options)

如果您想在运行时而不是在 Modelfile 中为模型设置自定义选项，则可以使用 options 参数进行设置。此示例设置了所有可用选项，但您可以单独设置其中任何一个选项，并忽略您不想覆盖的选项。

Request

curl http://localhost:11434/api/generate -d '{
  "model": "llama3",
  "prompt": "Why is the sky blue?",
  "stream": false,
  "options": {
    "num_keep": 5,
    "seed": 42,
    "num_predict": 100,
    "top_k": 20,
    "top_p": 0.9,
    "tfs_z": 0.5,
    "typical_p": 0.7,
    "repeat_last_n": 33,
    "temperature": 0.8,
    "repeat_penalty": 1.2,
    "presence_penalty": 1.5,
    "frequency_penalty": 1.0,
    "mirostat": 1,
    "mirostat_tau": 0.8,
    "mirostat_eta": 0.6,
    "penalize_newline": true,
    "stop": ["\n", "user:"],
    "numa": false,
    "num_ctx": 1024,
    "num_batch": 2,
    "num_gpu": 1,
    "main_gpu": 0,
    "low_vram": false,
    "f16_kv": true,
    "vocab_only": false,
    "use_mmap": true,
    "use_mlock": false,
    "num_thread": 8
  }
}'

Response

{
  "model": "llama3",
  "created_at": "2023-08-04T19:22:45.499127Z",
  "response": "The sky is blue because it is the color of the sky.",
  "done": true,
  "context": [1, 2, 3],
  "total_duration": 4935886791,
  "load_duration": 534986708,
  "prompt_eval_count": 26,
  "prompt_eval_duration": 107345000,
  "eval_count": 237,
  "eval_duration": 4289432000
}

加载模型

如果提供空的提示，模型将被加载到内存中。

Request

curl http://localhost:11434/api/generate -d '{
  "model": "llama3"
}'

Response

返回单个 JSON 对象：

{
  "model": "llama3",
  "created_at": "2023-12-18T19:52:07.071755Z",
  "response": "",
  "done": true
}

Generate 多轮对话（Chat Completion）

POST /api/chat

在一个对话中使用提供的模型生成下一条消息。这是一个流式端点，因此会有一系列响应。可以使用 "stream": false 禁用流式传输。最终响应对象将包括来自请求的统计信息和其他数据。

参数

model: (必需) 模型名称
messages: 聊天消息，可用于保存聊天记忆

该 message 对象具有以下字段：

role: 消息的角色, system, user 或 assistant
content: 消息内容
images (可选): 要包含在消息中的图像列表（用于多模态模型，例如llava）

高级参数（可选）：

format: 返回响应的格式。目前唯一接受的值是 json
options: additional model parameters listed in the documentation for the Modelfile such as temperature
stream: 如果 false 响应将作为单个响应对象返回，而不是对象流
keep_alive: 控制模型在请求后保持加载到内存中的时间 (默认: 5m)

示例

Chat Request (Streaming)

Request

流式响应发送聊天消息。

curl http://localhost:11434/api/chat -d '{
  "model": "llama3",
  "messages": [
    {
      "role": "user",
      "content": "why is the sky blue?"
    }
  ]
}'

Response

返回 JSON 对象流：

{
  "model": "llama3",
  "created_at": "2023-08-04T08:52:19.385406455-07:00",
  "message": {
    "role": "assistant",
    "content": "The",
    "images": null
  },
  "done": false
}

最终响应:

{
  "model": "llama3",
  "created_at": "2023-08-04T19:22:45.499127Z",
  "done": true,
  "total_duration": 4883583458,
  "load_duration": 1334875,
  "prompt_eval_count": 26,
  "prompt_eval_duration": 342546000,
  "eval_count": 282,
  "eval_duration": 4535599000
}

Chat request (No streaming)

Request

curl http://localhost:11434/api/chat -d '{
  "model": "llama3",
  "messages": [
    {
      "role": "user",
      "content": "why is the sky blue?"
    }
  ],
  "stream": false
}'

Response

{
  "model": "registry.ollama.ai/library/llama3:latest",
  "created_at": "2023-12-12T14:13:43.416799Z",
  "message": {
    "role": "assistant",
    "content": "Hello! How are you today?"
  },
  "done": true,
  "total_duration": 5191566416,
  "load_duration": 2154458,
  "prompt_eval_count": 26,
  "prompt_eval_duration": 383809000,
  "eval_count": 298,
  "eval_duration": 4799921000
}

Chat request (With History)

发送带有对话历史记录的聊天消息。您可以使用 multi-shot 或 chain-of-thought 通过提示相同的方法来开始对话。

Request

curl http://localhost:11434/api/chat -d '{
  "model": "llama3",
  "messages": [
    {
      "role": "user",
      "content": "why is the sky blue?"
    },
    {
      "role": "assistant",
      "content": "due to rayleigh scattering."
    },
    {
      "role": "user",
      "content": "how is that different than mie scattering?"
    }
  ]
}'

Response

返回 JSON 对象流：

{
  "model": "llama3",
  "created_at": "2023-08-04T08:52:19.385406455-07:00",
  "message": {
    "role": "assistant",
    "content": "The"
  },
  "done": false
}

最终响应:

{
  "model": "llama3",
  "created_at": "2023-08-04T19:22:45.499127Z",
  "done": true,
  "total_duration": 8113331500,
  "load_duration": 6396458,
  "prompt_eval_count": 61,
  "prompt_eval_duration": 398801000,
  "eval_count": 468,
  "eval_duration": 7701267000
}

Chat request (with images)

Request

发送带有对话历史记录的聊天消息。

curl http://localhost:11434/api/chat -d '{
  "model": "llava",
  "messages": [
    {
      "role": "user",
      "content": "what is in this image?",
      "images": ["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"]
    }
  ]
}'

Response

{
  "model": "llava",
  "created_at": "2023-12-13T22:42:50.203334Z",
  "message": {
    "role": "assistant",
    "content": " The image features a cute, little pig with an angry facial expression. It's wearing a heart on its shirt and is waving in the air. This scene appears to be part of a drawing or sketching project.",
    "images": null
  },
  "done": true,
  "total_duration": 1668506709,
  "load_duration": 1986209,
  "prompt_eval_count": 26,
  "prompt_eval_duration": 359682000,
  "eval_count": 83,
  "eval_duration": 1303285000
}

Chat request (Reproducible outputs)

Request

curl http://localhost:11434/api/chat -d '{
  "model": "llama3",
  "messages": [
    {
      "role": "user",
      "content": "Hello!"
    }
  ],
  "options": {
    "seed": 101,
    "temperature": 0
  }
}'

Response

{
  "model": "registry.ollama.ai/library/llama3:latest",
  "created_at": "2023-12-12T14:13:43.416799Z",
  "message": {
    "role": "assistant",
    "content": "Hello! How are you today?"
  },
  "done": true,
  "total_duration": 5191566416,
  "load_duration": 2154458,
  "prompt_eval_count": 26,
  "prompt_eval_duration": 383809000,
  "eval_count": 298,
  "eval_duration": 4799921000
}

创建模型

POST /api/create

从 Modelfile 创建模型。建议将modelfile 设置为 Modelfile 的内容，而不仅仅是设置path。这是远程创建的要求。远程模型创建还必须使用[create a Blob]（#create-a-Blob）和响应中指示的路径值，显式地与服务器一起创建任何文件Blob，如FROM 和ADAPTER字段。

参数

name: name of the model to create
modelfile (optional): contents of the Modelfile
stream: (optional) if false the response will be returned as a single response object, rather than a stream of objects
path (optional): path to the Modelfile

示例

创建一个新模型

从 Modelfile 创建一个新的模型

Request

curl http://localhost:11434/api/create -d '{
  "name": "mario",
  "modelfile": "FROM llama3\nSYSTEM You are mario from Super Mario Bros."
}'

Response

JSON 对象流。请注意，最终的 JSON 对象显示为 "status": "success".

{"status":"reading model metadata"}
{"status":"creating system layer"}
{"status":"using already created layer sha256:22f7f8ef5f4c791c1b03d7eb414399294764d7cc82c7e94aa81a1feb80a983a2"}
{"status":"using already created layer sha256:8c17c2ebb0ea011be9981cc3922db8ca8fa61e828c5d3f44cb6ae342bf80460b"}
{"status":"using already created layer sha256:7c23fb36d80141c4ab8cdbb61ee4790102ebd2bf7aeff414453177d4f2110e5d"}
{"status":"using already created layer sha256:2e0493f67d0c8c9c68a8aeacdf6a38a2151cb3c4c1d42accf296e19810527988"}
{"status":"using already created layer sha256:2759286baa875dc22de5394b4a925701b1896a7e3f8e53275c36f75a877a82c9"}
{"status":"writing layer sha256:df30045fe90f0d750db82a058109cecd6d4de9c90a3d75b19c09e5f64580bb42"}
{"status":"writing layer sha256:f18a68eb09bf925bb1b669490407c1b1251c5db98dc4d3d81f3088498ea55690"}
{"status":"writing manifest"}
{"status":"success"}

检查 Blob 是否存在

HEAD /api/blobs/:digest

确保用于 FROM 或 ADAPTER 字段的文件 blob 存在于服务器上。这将检查您的 Ollama 服务器，而不是 Ollama.ai。

查询参数

digest: blob 的 SHA256 摘要

示例

Request

curl -I http://localhost:11434/api/blobs/sha256:29fdb92e57cf0827ded04ae6461b5931d01fa595843f55d36f5b275a52087dd2

Response

Return 200 OK if the blob exists, 404 Not Found if it does not.

Create a Blob

POST /api/blobs/:digest

Create a blob from a file on the server. Returns the server file path.

Query Parameters

digest: the expected SHA256 digest of the file

示例

Request

curl -T model.bin -X POST http://localhost:11434/api/blobs/sha256:29fdb92e57cf0827ded04ae6461b5931d01fa595843f55d36f5b275a52087dd2

Response

Return 201 Created if the blob was successfully created, 400 Bad Request if the digest used is not expected.

List Local Models

GET /api/tags

List models that are available locally.

示例

Request

curl http://localhost:11434/api/tags

Response

A single JSON object will be returned.

{
  "models": [
    {
      "name": "codellama:13b",
      "modified_at": "2023-11-04T14:56:49.277302595-07:00",
      "size": 7365960935,
      "digest": "9f438cb9cd581fc025612d27f7c1a6669ff83a8bb0ed86c94fcf4c5440555697",
      "details": {
        "format": "gguf",
        "family": "llama",
        "families": null,
        "parameter_size": "13B",
        "quantization_level": "Q4_0"
      }
    },
    {
      "name": "llama3:latest",
      "modified_at": "2023-12-07T09:32:18.757212583-08:00",
      "size": 3825819519,
      "digest": "fe938a131f40e6f6d40083c9f0f430a515233eb2edaa6d72eb85c50d64f2300e",
      "details": {
        "format": "gguf",
        "family": "llama",
        "families": null,
        "parameter_size": "7B",
        "quantization_level": "Q4_0"
      }
    }
  ]
}

Show Model Information

POST /api/show

Show information about a model including details, modelfile, template, parameters, license, system prompt.

Parameters

name: name of the model to show
verbose: (optional) if set to true, returns full data for verbose response fields

示例

Request

curl http://localhost:11434/api/show -d '{
  "name": "llama3"
}'

Response

{
  "modelfile": "# Modelfile generated by \"ollama show\"\n# To build a new Modelfile based on this one, replace the FROM line with:\n# FROM llava:latest\n\nFROM /Users/matt/.ollama/models/blobs/sha256:200765e1283640ffbd013184bf496e261032fa75b99498a9613be4e94d63ad52\nTEMPLATE \"\"\"{{ .System }}\nUSER: {{ .Prompt }}\nASSISTANT: \"\"\"\nPARAMETER num_ctx 4096\nPARAMETER stop \"\u003c/s\u003e\"\nPARAMETER stop \"USER:\"\nPARAMETER stop \"ASSISTANT:\"",
  "parameters": "num_keep                       24\nstop                           \"<|start_header_id|>\"\nstop                           \"<|end_header_id|>\"\nstop                           \"<|eot_id|>\"",
  "template": "{{ if .System }}<|start_header_id|>system<|end_header_id|>\n\n{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ .Response }}<|eot_id|>",
  "details": {
    "parent_model": "",
    "format": "gguf",
    "family": "llama",
    "families": [
      "llama"
    ],
    "parameter_size": "8.0B",
    "quantization_level": "Q4_0"
  },
  "model_info": {
    "general.architecture": "llama",
    "general.file_type": 2,
    "general.parameter_count": 8030261248,
    "general.quantization_version": 2,
    "llama.attention.head_count": 32,
    "llama.attention.head_count_kv": 8,
    "llama.attention.layer_norm_rms_epsilon": 0.00001,
    "llama.block_count": 32,
    "llama.context_length": 8192,
    "llama.embedding_length": 4096,
    "llama.feed_forward_length": 14336,
    "llama.rope.dimension_count": 128,
    "llama.rope.freq_base": 500000,
    "llama.vocab_size": 128256,
    "tokenizer.ggml.bos_token_id": 128000,
    "tokenizer.ggml.eos_token_id": 128009,
    "tokenizer.ggml.merges": [],            // populates if `verbose=true`
    "tokenizer.ggml.model": "gpt2",
    "tokenizer.ggml.pre": "llama-bpe",
    "tokenizer.ggml.token_type": [],        // populates if `verbose=true`
    "tokenizer.ggml.tokens": []             // populates if `verbose=true`
  }
}

Copy a Model

POST /api/copy

Copy a model. Creates a model with another name from an existing model.

示例

Request

curl http://localhost:11434/api/copy -d '{
  "source": "llama3",
  "destination": "llama3-backup"
}'

Response

Returns a 200 OK if successful, or a 404 Not Found if the source model doesn’t exist.

Delete a Model

DELETE /api/delete

Delete a model and its data.

Parameters

name: model name to delete

示例

Request

curl -X DELETE http://localhost:11434/api/delete -d '{
  "name": "llama3:13b"
}'

Response

Returns a 200 OK if successful, 404 Not Found if the model to be deleted doesn’t exist.

Pull a Model

POST /api/pull

Download a model from the ollama library. Cancelled pulls are resumed from where they left off, and multiple calls will share the same download progress.

Parameters

name: name of the model to pull
insecure: (optional) allow insecure connections to the library. Only use this if you are pulling from your own library during development.
stream: (optional) if false the response will be returned as a single response object, rather than a stream of objects

示例

Request

curl http://localhost:11434/api/pull -d '{
  "name": "llama3"
}'

Response

If stream is not specified, or set to true, a stream of JSON objects is returned:

The first object is the manifest:

{
  "status": "pulling manifest"
}

Then there is a series of downloading responses. Until any of the download is completed, the completed key may not be included. The number of files to be downloaded depends on the number of layers specified in the manifest.

{
  "status": "downloading digestname",
  "digest": "digestname",
  "total": 2142590208,
  "completed": 241970
}

After all the files are downloaded, the final responses are:

{
    "status": "verifying sha256 digest"
}
{
    "status": "writing manifest"
}
{
    "status": "removing any unused layers"
}
{
    "status": "success"
}

if stream is set to false, then the response is a single JSON object:

{
  "status": "success"
}

Push a Model

POST /api/push

Upload a model to a model library. Requires registering for ollama.ai and adding a public key first.

Parameters

name: name of the model to push in the form of <namespace>/<model>:<tag>
insecure: (optional) allow insecure connections to the library. Only use this if you are pushing to your library during development.
stream: (optional) if false the response will be returned as a single response object, rather than a stream of objects

示例

Request

curl http://localhost:11434/api/push -d '{
  "name": "mattw/pygmalion:latest"
}'

Response

如果 stream 未指定或设置为 true, 则返回 JSON 对象流：

{ "status": "retrieving manifest" }

进而：

{
  "status": "starting upload",
  "digest": "sha256:bc07c81de745696fdf5afca05e065818a8149fb0c77266fb584d9b2cba3711ab",
  "total": 1928429856
}

然后是一系列的上传响应：

{
  "status": "starting upload",
  "digest": "sha256:bc07c81de745696fdf5afca05e065818a8149fb0c77266fb584d9b2cba3711ab",
  "total": 1928429856
}

最后，当上传完成时：

{"status":"pushing manifest"}
{"status":"success"}

如果 stream 设置为 false, 则响应是单个 JSON 对象：

{ "status": "success" }

Generate Embeddings

POST /api/embeddings

从模型生成嵌入

参数

model: 生成嵌入的模型名称
prompt: 要生成嵌入的文本

高级参数:

options: Modelfile 文档中列出的其他模型参数，例如 temperature
keep_alive: 控制模型在请求后保持加载到内存中的时间 (默认: 5m)

示例

Request

curl http://localhost:11434/api/embeddings -d '{
  "model": "all-minilm",
  "prompt": "Here is an article about llamas..."
}'

Response

{
  "embedding": [
    0.5670403838157654, 0.009260174818336964, 0.23178744316101074, -0.2916173040866852, -0.8924556970596313,
    0.8785552978515625, -0.34576427936553955, 0.5742510557174683, -0.04222835972905159, -0.137906014919281
  ]
}

列出正在运行的模型

GET /api/ps

列出当前加载到内存中的模型。

示例

Request

curl http://localhost:11434/api/ps

Response

将返回单个 JSON 对象。

{
  "models": [
    {
      "name": "mistral:latest",
      "model": "mistral:latest",
      "size": 5137025024,
      "digest": "2ae6f6dd7a3dd734790bbbf58b8909a606e0e7e97e94b7604e0aa7ae4490e6d8",
      "details": {
        "parent_model": "",
        "format": "gguf",
        "family": "llama",
        "families": [
          "llama"
        ],
        "parameter_size": "7.2B",
        "quantization_level": "Q4_0"
      },
      "expires_at": "2024-06-04T14:38:31.83753-07:00",
      "size_vram": 5137025024
    }
  ]
}

https://github.com/ollama/ollama/blob/main/docs/api.md

https://github.com/ollama/ollama/blob/main/docs/openai.md

作者：Jeebiz 创建时间：2024-04-24 09:27
最后编辑：Jeebiz 更新时间：2024-11-21 01:00