This is a collection of JS libraries to interact with the Hugging Face API, with TS types included.
- @huggingface/hub: Interact with huggingface.co to create or delete repos and commit / download files
- @huggingface/inference: Use the Inference API to make calls to 100,000+ Machine Learning models!
With more to come, like @huggingface/endpoints
to manage your HF Endpoints!
We use modern features to avoid polyfills and dependencies, so the libraries will only work on modern browsers / Node.js >= 18 / Bun / Deno.
The libraries are still very young, please help us by opening issues!
To install via NPM, you can download the libraries as needed:
npm install @huggingface/hub
npm install @huggingface/inference
Then import the libraries in your code:
import { createRepo, commit, deleteRepo, listFiles } from "@huggingface/hub";
import { HfInference } from "@huggingface/inference";
import type { RepoId, Credentials } from "@huggingface/hub";
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/+esm';
import { createRepo, commit, deleteRepo, listFiles } from "https://cdn.jsdelivr.net/npm/@huggingface/hub@0/+esm";
</script>
import { createRepo, commit } from "@huggingface/hub";
import { HfInference } from "@huggingface/inference";
// use an access token from your free account
const HF_ACCESS_TOKEN = "hf_...";
await createRepo({
repo: {type: "model", name: "my-user/nlp-test"},
credentials: {accessToken: HF_ACCESS_TOKEN}
});
await commit({
repo: {type: "model", name: "my-user/nlp-test"},
credentials: {accessToken: HF_ACCESS_TOKEN},
title: "Add model file",
operations: [{
operation: "addOrUpdate",
path: "pytorch_model.bin",
content: new Blob(...) // Can work with native File in browsers
}]
});
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]',
negative_prompt: 'blurry',
model: 'stabilityai/stable-diffusion-2',
})
There are more features of course, check each library's README!
pnpm install
pnpm -r format
pnpm -r test
pnpm -r build
This will generate ESM and CJS javascript files in packages/*/dist
, eg packages/inference/dist/index.mjs
.