This is a collection of JS libraries to interact with the Hugging Face API, with TS types included.

We use modern features to avoid polyfills and dependencies, so the libraries will only work on modern browsers / Node.js >= 18 / Bun / Deno.

Installation

From NPM

npm install @huggingface/hub
npm install @huggingface/inference

import { createRepo, commit, deleteRepo, listFiles } from "@huggingface/hub";
import { HfInference } from "@huggingface/inference";
import type { RepoId, Credentials } from "@huggingface/hub";

From CDN or Static hosting

You can run our packages with vanilla JS, without any bundler, by using a CDN or static hosting. Using ES modules, i.e. <script type="module">, you can import the libraries in your code:


<script type="module">
    import { HfInference } from 'https://cdn.jsdelivr.net/npm/@huggingface/inference@1.8.0/+esm';
    import { createRepo, commit, deleteRepo, listFiles } from "https://cdn.jsdelivr.net/npm/@huggingface/hub@0.5.0/+esm";
</script>

Usage example

import { createRepo, uploadFile, deleteFiles } from "@huggingface/hub";
import { HfInference } from "@huggingface/inference";

// use an access token from your free account
const HF_ACCESS_TOKEN = "hf_...";

await createRepo({
  repo: "my-user/nlp-model", // or {type: "model", name: "my-user/nlp-test"},
  credentials: {accessToken: HF_ACCESS_TOKEN}
});

await uploadFile({
  repo: "my-user/nlp-model",
  credentials: {accessToken: HF_ACCESS_TOKEN},
  // Can work with native File in browsers
  file: {
    path: "pytorch_model.bin",
    content: new Blob(...) 
  }
});

await deleteFiles({
  repo: {type: "space", name: "my-user/my-space"}, // or "spaces/my-user/my-space"
  credentials: {accessToken: HF_ACCESS_TOKEN},
  paths: ["README.md", ".gitattributes"]
});

const inference = new HfInference(HF_ACCESS_TOKEN);

await inference.translation({
  model: 't5-base',
  inputs: 'My name is Wolfgang and I live in Berlin'
})

await inference.textToImage({
  inputs: 'award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]',
  model: 'stabilityai/stable-diffusion-2',
  parameters: {
    negative_prompt: 'blurry',
  }
})

await inference.imageToText({
  data: await (await fetch('https://picsum.photos/300/300')).blob(),
  model: 'nlpconnect/vit-gpt2-image-captioning',  
})

Formatting & testing

pnpm install

pnpm -r format:check
pnpm -r lint:check
pnpm -r test

Building