// Programmatically interact with the Hub

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

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

// Use all supported Inference Providers!

await inference.chatCompletion({
  model: "meta-llama/Llama-3.1-8B-Instruct",
  provider: "sambanova", // or together, fal-ai, replicate, cohere …
  messages: [
    {
      role: "user",
      content: "Hello, nice to meet you!",
    },
  ],
  max_tokens: 512,
  temperature: 0.5,
});

await inference.textToImage({
  model: "black-forest-labs/FLUX.1-dev",
  provider: "replicate",
  inputs: "a picture of a green bird",
});

// and much more…

Hugging Face JS libraries

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 all supported (serverless) Inference Providers or switch to Inference Endpoints (dedicated) to make calls to 100,000+ Machine Learning models
• @huggingface/mcp-client: A Model Context Protocol (MCP) client, and a tiny Agent library, built on top of InferenceClient.
• @huggingface/gguf: A GGUF parser that works on remotely hosted files.
• @huggingface/dduf: Similar package for DDUF (DDUF Diffusers Unified Format)
• @huggingface/lerobot: A parser for LeRobot robotics datasets, reading v2.x and v3.0 layouts over ranged HTTP requests.
• @huggingface/usd-web-viewer: An OpenUSD viewer for the web: composes .usd, .usda, .usdc and .usdz files in WebAssembly and renders them with three.js.
• @huggingface/tasks: The definition files and source-of-truth for the Hub's main primitives like pipeline tasks, model libraries, etc.
• @huggingface/jinja: A minimalistic JS implementation of the Jinja templating engine, to be used for ML chat templates.
• @huggingface/space-header: Use the Space mini_header outside Hugging Face
• @huggingface/ollama-utils: Various utilities for maintaining Ollama compatibility with models on the Hugging Face Hub.
• @huggingface/tiny-agents: A tiny, model-agnostic library for building AI agents that can use tools.

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!

Installation

From NPM

To install via NPM, you can download the libraries as needed:

npm install @huggingface/hub
npm install @huggingface/inference
npm install @huggingface/mcp-client

Then import the libraries in your code:

import { createRepo, commit, deleteRepo, listFiles } from "@huggingface/hub";
import { InferenceClient } from "@huggingface/inference";
import { McpClient } from "@huggingface/mcp-client";
import type { RepoId } 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 { InferenceClient } from 'https://cdn.jsdelivr.net/npm/@huggingface/[email protected]/+esm';
    import { createRepo, commit, deleteRepo, listFiles } from "https://cdn.jsdelivr.net/npm/@huggingface/[email protected]/+esm";
</script>

Deno

// esm.sh
import { InferenceClient } from "https://esm.sh/@huggingface/inference"

import { createRepo, commit, deleteRepo, listFiles } from "https://esm.sh/@huggingface/hub"
// or npm:
import { InferenceClient } from "npm:@huggingface/inference"

import { createRepo, commit, deleteRepo, listFiles } from "npm:@huggingface/hub"

Usage examples

Get your HF access token in your account settings.

This is the beginning of the README. Read the rest at the original. Read the full README ↗