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🤗 Hugging Face Hub API

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🤗 Hugging Face Hub API

用于使用 Hugging Face Hub API 的官方实用工具。

安装

pnpm add @huggingface/hub

npm add @huggingface/hub

yarn add @huggingface/hub

Deno

// esm.sh
import { uploadFiles, listModels } from "https://esm.sh/@huggingface/hub"
// or npm:
import { uploadFiles, listModels } from "npm:@huggingface/hub"

用法

对于某些调用,您需要创建一个账户并生成一个访问令牌。

在本交互式教程中,学习如何使用 hub 包查找免费模型。

import * as hub from "@huggingface/hub";
import type { RepoDesignation } from "@huggingface/hub";

const repo: RepoDesignation = { type: "model", name: "myname/some-model" };

const {name: username} = await hub.whoAmI({accessToken: "hf_..."});

for await (const model of hub.listModels({search: {owner: username}, accessToken: "hf_..."})) {
  console.log("My model:", model);
}

const specificModel = await hub.modelInfo({name: "openai-community/gpt2"});
await hub.checkRepoAccess({repo, accessToken: "hf_..."});

await hub.createRepo({ repo, accessToken: "hf_...", license: "mit" });

await hub.uploadFiles({
  repo,
  accessToken: "hf_...",
  files: [
    // path + blob content
    {
      path: "file.txt",
      content: new Blob(["Hello World"]),
    },
    // Local file URL
    pathToFileURL("./pytorch-model.bin"),
    // Local folder URL
    pathToFileURL("./models"),
    // Web URL
    new URL("https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json"),
    // Path + Web URL
    {
      path: "myfile.bin",
      content: new URL("https://huggingface.co/bert-base-uncased/resolve/main/pytorch_model.bin")
    }
    // Can also work with native File in browsers
  ],
});

// or

for await (const progressEvent of await hub.uploadFilesWithProgress({
  repo,
  accessToken: "hf_...",
  files: [
    ...
  ],
})) {
  console.log(progressEvent);
}

// Edit a file in place, without downloading/uploading its unchanged data
const file = await hub.downloadFile({ repo, path: "myfile.bin", accessToken: "hf_..." });
await hub.uploadFile({
  repo,
  accessToken: "hf_...",
  file: {
    path: "myfile.bin",
    originalContent: file,
    edits: [{
      // Replace bytes [0, 4)
      start: 0,
      end: 4,
      content: new Blob(["new prefix"])
    }, {
      // Append at the end
      start: file.size,
      end: file.size,
      content: new Blob(["suffix"])
    }]
  }
});

await hub.deleteFile({repo, accessToken: "hf_...", path: "myfile.bin"});

await (await hub.downloadFile({ repo, path: "README.md" })).text();

for await (const fileInfo of hub.listFiles({repo})) {
  console.log(fileInfo);
}

await hub.deleteRepo({ repo, accessToken: "hf_..." });

桶

存储桶是 Hub 上可变的、非版本化的存储。使用 buckets/ 前缀(或 { type: "bucket", name })配合相同的函数:

const bucket = "buckets/myname/my-bucket";

await hub.createRepo({ repo: bucket, accessToken: "hf_..." });

await hub.uploadFiles({ repo: bucket, accessToken: "hf_...", files: [pathToFileURL("./checkpoints")] });

for await (const fileInfo of hub.listFiles({ repo: bucket, recursive: true, accessToken: "hf_..." })) {
  console.log(fileInfo.path, fileInfo.uploadedAt);
}

// Copy files from a model or dataset repo into a bucket server-side, without downloading them
await hub.copyFolder({
  source: { repo: { type: "dataset", name: "myname/my-dataset" }, path: "data" },
  destination: { repo: bucket, path: "data" },
  accessToken: "hf_...",
});

CLI 用法

您可以在 CLI 模式下使用 @huggingface/hub 将文件和文件夹上传到或从您的仓库下载。

npx @huggingface/hub upload coyotte508/test-model .
npx @huggingface/hub upload datasets/coyotte508/test-dataset .
# Same thing
npx @huggingface/hub upload --repo-type dataset coyotte508/test-dataset .
# Upload new data with 0 history in a separate branch
npx @huggingface/hub branch create coyotte508/test-model release --empty
npx @huggingface/hub upload coyotte508/test-model . --revision release

# Download files to the current directory (or --local-dir)
npx @huggingface/hub download coyotte508/test-model config.json
npx @huggingface/hub download coyotte508/test-model config.json README.md --local-dir ./test-model
# Download an entire repo, optionally filtered with --include / --exclude
npx @huggingface/hub download coyotte508/test-model --local-dir ./test-model
npx @huggingface/hub download --repo-type dataset coyotte508/test-dataset --include "*.json"

npx @huggingface/hub --help
npx @huggingface/hub upload --help
npx @huggingface/hub download --help

您也可以使用 npm install -g @huggingface/hub 进行全局安装。然后您可以执行以下操作:

hfjs upload coyotte508/test-model .

hfjs branch create --repo-type dataset coyotte508/test-dataset release --empty
hfjs upload --repo-type dataset coyotte508/test-dataset . --revision release

hfjs download coyotte508/test-model config.json
hfjs download coyotte508/test-model --local-dir ./test-model

hfjs --help
hfjs  upload --help

hfjs help jobs
hfjs download --help

OAuth 登录

可以使用 OAuth(“使用 HF 登录”)进行登录。

这将使您能够获取访问令牌,以便使用部分 API,具体取决于 Space 或 OAuth App 中设置的权限范围。

import { oauthLoginUrl, oauthHandleRedirectIfPresent } from "@huggingface/hub";

const oauthResult = await oauthHandleRedirectIfPresent();

if (!oauthResult) {
  // If the user is not logged in, redirect to the login page
  window.location.href = await oauthLoginUrl();
}

// You can use oauthResult.accessToken, oauthResult.accessTokenExpiresAt and oauthResult.userInfo
console.log(oauthResult);

查看演示:https://huggingface.co/spaces/huggingfacejs/client-side-oauth

Hugging face 缓存

@huggingface/hub 包提供了扫描缓存目录的基本功能。有关 管理 huggingface_hub 缓存系统 的更多信息,请参阅相关文档。

scanCacheDir

您可以使用 scanCacheDir 函数获取缓存仓库的列表。

import { scanCacheDir } from "@huggingface/hub";

const result = await scanCacheDir();

console.log(result);

注意:此功能在浏览器中无法使用

downloadFileToCacheDir

您可以使用 downloadFileToCacheDir 函数来缓存仓库中的文件。

import { downloadFileToCacheDir } from "@huggingface/hub";

const file = await downloadFileToCacheDir({
  repo: 'foo/bar',
  path: 'README.md'
});

console.log(file);

注意:此功能在浏览器中无法使用

snapshotDownload

您可以使用 snapshotDownload 函数在缓存目录中下载指定修订版本的整个仓库。

import { snapshotDownload } from "@huggingface/hub";

const directory = await snapshotDownload({
  repo: 'foo/bar',
});

console.log(directory);

该代码内部使用了 downloadFileToCacheDir 函数。

注意:此功能在浏览器中无法使用

性能考量

在上传大文件时,您可能希望在 worker 中运行 commit 调用,以将 sha256 计算任务卸载出去。

在可能的情况下,远程资源和本地文件应作为 URL 传入,以便按块进行延迟加载,从而降低内存占用。在浏览器上下文中传入 File 也是可行的,因为它原生表现为 Blob。

在底层,@huggingface/hub 使用惰性 blob 实现来加载文件。

若要编辑现有文件,请优先使用 edit 提交操作,并将 downloadFile 返回的 blob 作为 originalContent:这样只会下载、重新分块并计算哈希值被编辑的区域。对于向同一文件进行多次追加操作,请在 commit 调用中传入共享的 rangeEditCache: new Map(),以同时跳过存储元数据的往返请求。

依赖

  • @huggingface/tasks : 仅类型定义
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