---
title: "AI Endpoints - Integration with Hugging Face Inference Providers"
description: "Find out how to use OVHcloud AI Endpoints through Hugging Face Inference Providers"
url: https://docs.ovhcloud.com/en/guides/public-cloud/ai-machine-learning/ai-endpoints-huggingface-integration
lang: en
lastUpdated: 2026-03-27
---
# AI Endpoints - Integration with Hugging Face Inference Providers

:::info
AI Endpoints is covered by the [OVHcloud AI Endpoints conditions](https://storage.gra.cloud.ovh.net/v1/AUTH_325716a587c64897acbef9a4a4726e38/contracts/48743bf-AI_Endpoints-ALL-1.1.pdf) and the [OVHcloud Public Cloud special conditions](https://storage.gra.cloud.ovh.net/v1/AUTH_325716a587c64897acbef9a4a4726e38/contracts/d2a208c-Conditions_particulieres_OVH_Stack-WE-9.0.pdf).
:::

**New integration available:** We're excited to announce a new integration for [AI Endpoints](https://www.ovhcloud.com/en-gb/public-cloud/ai-endpoints/) with [Hugging Face Inference Providers](https://huggingface.co/docs/inference-providers/index/). This integration offers streamlined, unified access to world-class inference partners, and continues our commitment to integrating AI Endpoints into as many open-source tools as possible to simplify its usage.

## Objective

OVHcloud [AI Endpoints](https://www.ovhcloud.com/en-gb/public-cloud/ai-endpoints/) allows developers to easily add AI features to their day-to-day developments.

In this guide, we will show how to use [Hugging Face Inference Providers](https://huggingface.co/docs/inference-providers/index/) to access OVHcloud [AI Endpoints](https://www.ovhcloud.com/en-gb/public-cloud/ai-endpoints/) models through Hugging Face's unified interface.

With Hugging Face's Inference Providers and OVHcloud's scalable AI infrastructure, you can access a wide range of AI models using familiar APIs, whether you're working in Python or JavaScript/TypeScript.

![Hugging Face](/images/public-cloud/ai-machine-learning/endpoints-tuto-18-huggingface-integration/header-huggingface.png)
## Definition

- [Hugging Face Inference Providers](https://huggingface.co/docs/inference-providers/index/): A platform that offers streamlined, unified access to hundreds of machine learning models powered by world-class inference partners. It provides a single interface to access models from multiple providers, including OVHcloud AI Endpoints, with flexible provider selection strategies.
- [AI Endpoints](https://www.ovhcloud.com/en-gb/public-cloud/ai-endpoints/): A serverless platform by OVHcloud providing easy access to a variety of world-renowned AI models including Mistral, LLaMA, and more. This platform is designed to be simple, secure, and intuitive with data privacy as a top priority.

### Why is this integration important?

This new integration offers you several advantages:

- **Unified access**: Access hundreds of models through a single, familiar interface.
- **Flexibility**: Choose between automatic, performance-based, or provider-specific selection.
- **Multi-language support**: Use Python or JavaScript/TypeScript with the same models.
- **OpenAI compatibility**: Use the OpenAI SDK for familiar syntax.
- **Cost control**: Choose between Hugging Face billing or Bring Your Own Key (BYOK) with OVHcloud AI Endpoints.

## Requirements

Before getting started, make sure you have:

1. An OVHcloud account with access to AI Endpoints.
2. A Hugging Face account (sign up at [huggingface.co](https://huggingface.co/join)).
3. A Hugging Face access token with "Make calls to Inference Providers" permissions (create at [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens)).
4. Python 3.8 or higher (for Python usage) or Node.js (for JavaScript/TypeScript usage).
5. Optionally, an OVHcloud AI Endpoints API key for Bring Your Own Key (BYOK) billing.

![Generate an API key](/images/public-cloud/ai-machine-learning/endpoints-tuto-18-huggingface-integration/generate_an_api_key.png)
## Instructions

### Installation

#### Python

Install the required packages via pip:

```bash
pip install huggingface_hub
```

Then, you can authenticate yourself with:

```bash
hf auth login # get a read token from hf.co/settings/tokens
```

or add your key to the environment variable `export HF_TOKEN=...`.

You are now ready to get started.

#### JavaScript / TypeScript

Install the required packages via npm:

```bash
npm install @huggingface/inference
```

And add your key to the environment variable `export HF_TOKEN=...`.

You can now get started.

### Basic configuration

#### Bring Your Own Key (BYOK)

You can also use your OVHcloud AI Endpoints API key directly for billing through OVHcloud instead of Hugging Face. To enable this:

1. Go to [Hugging Face Inference Providers settings](https://huggingface.co/settings/inference-providers/settings).
2. Add your OVHcloud AI Endpoints API key.
3. Usage will be billed directly to your OVHcloud PCI project.

### Basic usage

#### Python - using OpenAI SDK

Here's a simple usage example using the OpenAI SDK:

```python
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://router.huggingface.co/v1",
    api_key=os.environ["HF_TOKEN"],
)

completion = client.chat.completions.create(
    model="openai/gpt-oss-120b:ovhcloud",
    messages=[
        {
            "role": "system",
            "content": "You are a helpful AI assistant."
        },
        {
            "role": "user",
            "content": "What is the capital of France?"
        }
    ],
    temperature=0.7,
    max_tokens=100,
)

print(completion.choices[0].message.content)
```

#### Python - using Hugging Face Hub client

Alternatively, use the native Hugging Face Hub client:

```python
from huggingface_hub import InferenceClient

client = InferenceClient(
  provider="ovhcloud",
  api_key=os.environ["HF_TOKEN"]
)

completion = client.chat.completions.create(
    model="openai/gpt-oss-120b:ovhcloud",
    messages=[
        {
            "role": "user",
            "content": "How many 'G's in 'huggingface'?"
        }
    ],
)

print(completion.choices[0].message)
```

#### JavaScript - using Hugging Face Inference client

Here's a simple usage example in JavaScript:

```javascript
import { InferenceClient } from "@huggingface/inference";

const client = new InferenceClient(process.env.HF_TOKEN);

const chatCompletion = await client.chatCompletion({
  model: "openai/gpt-oss-120b:ovhcloud",
  messages: [
    {
      role: "user",
      content: "How many 'G's in 'huggingface'?",
    },
  ],
});

console.log(chatCompletion.choices[0].message);
```

#### JavaScript - using OpenAI SDK

You can also use the OpenAI SDK in JavaScript:

```javascript
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://router.huggingface.co/v1",
  apiKey: process.env.HF_TOKEN,
});

const completion = await client.chat.completions.create({
  model: "openai/gpt-oss-120b:ovhcloud",
  messages: [
    {
      role: "user",
      content: "How many 'G's in 'huggingface'?",
    },
  ],
});

console.log(completion.choices[0].message.content);
```

### Advanced features

#### Provider selection strategies

Hugging Face offers flexible provider selection strategies to optimize for your needs:

**Automatic selection (default)**

Uses the first available provider based on your preference order:

`openai/gpt-oss-120b`

**Specific provider**

Force the OVHcloud provider:

`openai/gpt-oss-120b:ovhcloud`

**Performance-based selection**

Select the fastest provider (highest throughput):

`openai/gpt-oss-120b:fastest`

Select the cheapest provider (lowest cost per token):

`openai/gpt-oss-120b:cheapest`

**Setting provider preferences**

Configure your preferred provider order at [huggingface.co/settings/inference-providers](https://huggingface.co/settings/inference-providers).

### Available models

OVHcloud AI Endpoints offers a wide range of models accessible via Hugging Face Inference Providers. For the complete and up-to-date list, visit our [model catalog](https://www.ovhcloud.com/en-gb/public-cloud/ai-endpoints/catalog/) or browse [OVHcloud models on Hugging Face](https://huggingface.co/models?inference_provider=ovhcloud\&sort=trending).

### Pricing and billing

Hugging Face Inference Providers uses a pay-as-you-go model with flexible billing options:

- **Hugging Face billing**: Usage is billed directly to your Hugging Face account.
- **No setup costs**: No infrastructure or commitment required.
- **Cost control**: Monitor usage in your [Hugging Face settings](https://huggingface.co/settings/billing).
- **Bring Your Own Key (BYOK)**: Use your OVHcloud AI Endpoints API key to be billed directly by OVHcloud instead of Hugging Face. Configure this in [Hugging Face Inference Providers settings](https://huggingface.co/settings/inference-providers/settings).

### Conclusion

In this article, we explored how to integrate OVHcloud AI Endpoints with Hugging Face Inference Providers to seamlessly access a wide range of AI models through a unified interface. Thanks to Hugging Face's Inference Providers, you can use familiar APIs in Python or JavaScript/TypeScript, with flexible provider selection and billing options, while OVHcloud AI Endpoints ensures secure, scalable, and production-ready AI infrastructure.

## Go further

You can find more information about Hugging Face Inference Providers on their [official documentation](https://huggingface.co/docs/inference-providers/). You can also browse the [AI Endpoints catalog](https://www.ovhcloud.com/en-gb/public-cloud/ai-endpoints/catalog/) to explore the models that are available.

For detailed information about OVHcloud on Hugging Face Inference Providers, visit the [OVHcloud provider documentation](https://huggingface.co/docs/inference-providers/providers/ovhcloud/).

Browse [OVHcloud models on Hugging Face](https://huggingface.co/models?inference_provider=ovhcloud\&sort=trending) to discover all available models.

For more information about the Hugging Face Hub Python library, visit the [official documentation](https://huggingface.co/docs/huggingface_hub/).

Browse the full [AI Endpoints documentation](/en/guides/public-cloud/ai-machine-learning/overview.md) to further understand the main concepts and get started.

If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](https://www.ovhcloud.com/en-gb/professional-services/) to get a quote and ask our Professional Services experts for a custom analysis of your project.

## Feedback

Please feel free to send us your questions, feedback, and suggestions regarding AI Endpoints and its features:

- In the #ai-endpoints channel of the OVHcloud [Discord server](https://discord.gg/ovhcloud), where you can engage with the community and OVHcloud team members.
- Join the Hugging Face community on [Discord](https://discord.com/invite/hugging-face-879548962464493619) for questions about Hugging Face Inference Providers.