// 程序化地与Hub交互
await createRepo({
repo: {type: "model", name: "my-user/nlp-model"},
credentials: {accessToken: HF_TOKEN}
});
await uploadFile({
repo: "my-user/nlp-model",
credentials: {accessToken: HF_TOKEN},
// 能在浏览器中处理原生文件
file: {
path: "pytorch_model.bin",
content: new Blob(...)
}
});
// 使用托管推理
await inference.translation({
model: 't5-base',
inputs: 'My name is Wolfgang and I live in Berlin'
})
await inference.textToImage({
model: 'stabilityai/stable-diffusion-2',
inputs: 'award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]',
parameters: {
negative_prompt: 'blurry',
}
})
// 还有更多……
Hugging Face JS库
这是一个用于与Hugging Face API交互的JS库集合,包括TS类型。
- @huggingface/inference: 使用推理端点(专用)和推理API(无服务器)调用超过100,000个机器学习模型
- @huggingface/hub: 与huggingface.co交互以创建或删除存储库以及提交/下载文件
- @huggingface/agents: 通过自然语言界面与HF模型交互
- @huggingface/gguf: 一个处理远程托管文件的GGUF解析器
- @huggingface/tasks: Hub主要原语(如pipeline任务,模型库等)的定义文件和真源
- @huggingface/space-header: 在Hugging Face之外使用Space
mini_header
组件
我们使用现代功能来避免填充和依赖,因此这些库仅能在现代浏览器/Node.js >= 18/Bun/Deno上运行。
这些库还非常年轻,欢迎通过提交问题来帮助我们!
安装
从NPM安装
要通过NPM安装,可以根据需要下载这些库:
npm install @huggingface/inference
npm install @huggingface/hub
npm install @huggingface/agents
然后在代码中导入这些库:
import { HfInference } from "@huggingface/inference";
import { HfAgent } from "@huggingface/agents";
import { createRepo, commit, deleteRepo, listFiles } from "@huggingface/hub";
import type { RepoId, Credentials } from "@huggingface/hub";
从CDN或静态托管安装
你可以使用CDN或静态托管在没有任何打包工具的情况下运行我们的包。使用ES模块,即<script type="module">
,你可以在代码中导入这些库:
<script type="module">
import { HfInference } from 'https://cdn.jsdelivr.net/npm/@huggingface/inference@2.8.0/+esm';
import { createRepo, commit, deleteRepo, listFiles } from "https://cdn.jsdelivr.net/npm/@huggingface/hub@0.15.1/+esm";
</script>
Deno安装
// esm.sh
import { HfInference } from "https://esm.sh/@huggingface/inference"
import { HfAgent } from "https://esm.sh/@huggingface/agents";
import { createRepo, commit, deleteRepo, listFiles } from "https://esm.sh/@huggingface/hub"
// 或npm:
import { HfInference } from "npm:@huggingface/inference"
import { HfAgent } from "npm:@huggingface/agents";
import { createRepo, commit, deleteRepo, listFiles } from "npm:@huggingface/hub"
使用示例
在账户设置中获取你的HF访问令牌。
@huggingface/inference 示例
import { HfInference } from "@huggingface/inference";
const HF_TOKEN = "hf_...";
const inference = new HfInference(HF_TOKEN);
// 聊天补全API
const out = await inference.chatCompletion({
model: "mistralai/Mistral-7B-Instruct-v0.2",
messages: [{ role: "user", content: "Complete the this sentence with words one plus one is equal " }],
max_tokens: 100
});
console.log(out.choices[0].message);
// 流式聊天补全API
for await (const chunk of inference.chatCompletionStream({
model: "mistralai/Mistral-7B-Instruct-v0.2",
messages: [{ role: "user", content: "Complete the this sentence with words one plus one is equal " }],
max_tokens: 100
})) {
console.log(chunk.choices[0].delta.content);
}
// 你也可以省略“model”以使用该任务的推荐模型
await inference.translation({
model: 't5-base',
inputs: 'My name is Wolfgang and I live in Amsterdam'
})
await inference.textToImage({
model: 'stabilityai/stable-diffusion-2',
inputs: 'award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]',
parameters: {
negative_prompt: 'blurry',
}
})
await inference.imageToText({
data: await (await fetch('https://picsum.photos/300/300')).blob(),
model: 'nlpconnect/vit-gpt2-image-captioning',
})
// 使用你自己的专用推理端点:https://hf.co/docs/inference-endpoints/
const gpt2 = inference.endpoint('https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2');
const { generated_text } = await gpt2.textGeneration({inputs: 'The answer to the universe is'});
//聊天补全
const mistal = inference.endpoint(
"https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.2"
);
const out = await mistal.chatCompletion({
model: "mistralai/Mistral-7B-Instruct-v0.2",
messages: [{ role: "user", content: "Complete the this sentence with words one plus one is equal " }],
max_tokens: 100,
});
console.log(out.choices[0].message);
@huggingface/hub 示例
import { createRepo, uploadFile, deleteFiles } from "@huggingface/hub";
const HF_TOKEN = "hf_...";
await createRepo({
repo: "my-user/nlp-model", // 或 {type: "model", name: "my-user/nlp-test"},
credentials: {accessToken: HF_TOKEN}
});
await uploadFile({
repo: "my-user/nlp-model",
credentials: {accessToken: HF_TOKEN},
// 能在浏览器中处理原生文件
file: {
path: "pytorch_model.bin",
content: new Blob(...)
}
});
await deleteFiles({
repo: {type: "space", name: "my-user/my-space"}, // 或 "spaces/my-user/my-space"
credentials: {accessToken: HF_TOKEN},
paths: ["README.md", ".gitattributes"]
});
@huggingface/agents 示例
import {HfAgent, LLMFromHub, defaultTools} from '@huggingface/agents';
const HF_TOKEN = "hf_...";
const agent = new HfAgent(
HF_TOKEN,
LLMFromHub(HF_TOKEN),
[...defaultTools]
);
// 你可以生成代码,检查它,然后运行它
const code = await agent.generateCode("Draw a picture of a cat wearing a top hat. Then caption the picture and read it out loud.");
console.log(code);
const messages = await agent.evaluateCode(code)
console.log(messages); // 包含数据
// 或者你可以直接运行代码,但这种方式你不能检查代码是否安全,因此要自行承担风险。
const messages = await agent.run("Draw a picture of a cat wearing a top hat. Then caption the picture and read it out loud.")
console.log(messages);
当然还有更多功能,请查看每个库的README!
格式化与测试
sudo corepack enable
pnpm install
pnpm -r format:check
pnpm -r lint:check
pnpm -r test
构建
pnpm -r build
这会在packages/*/dist
中生成ESM和CJS JavaScript文件,例如packages/inference/dist/index.mjs
。