> ## Documentation Index
> Fetch the complete documentation index at: https://docs.portkey.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Hugging Face

> Use Hugging Face Inference endpoints through Portkey for thousands of open-source models.

## Quick Start

Get started with Hugging Face in under 2 minutes:

```python Python icon="python" theme={"system"}
from portkey_ai import Portkey

# 1. Install: pip install portkey-ai
# 2. Add @huggingface provider in model catalog
# 3. Use it:

portkey = Portkey(api_key="PORTKEY_API_KEY")

response = portkey.chat.completions.create(
    model="@huggingface/meta-llama/Llama-3.2-3B-Instruct",
    messages=[{"role": "user", "content": "Hello!"}]
)

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

```js Javascript icon="square-js" theme={"system"}
import Portkey from 'portkey-ai'

// 1. Install: npm install portkey-ai
// 2. Add @huggingface provider in model catalog
// 3. Use it:

const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY"
})

const response = await portkey.chat.completions.create({
    model: "@huggingface/meta-llama/Llama-3.2-3B-Instruct",
    messages: [{ role: "user", content: "Hello!" }]
})

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

```python OpenAI Py icon="python" theme={"system"}
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL

# 1. Install: pip install openai portkey-ai
# 2. Add @huggingface provider in model catalog
# 3. Use it:

client = OpenAI(
    api_key="PORTKEY_API_KEY",  # Portkey API key
    base_url=PORTKEY_GATEWAY_URL
)

response = client.chat.completions.create(
    model="@huggingface/meta-llama/Llama-3.2-3B-Instruct",
    messages=[{"role": "user", "content": "Hello!"}]
)

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

```js OpenAI JS icon="square-js" theme={"system"}
import OpenAI from "openai"
import { PORTKEY_GATEWAY_URL } from "portkey-ai"

// 1. Install: npm install openai portkey-ai
// 2. Add @huggingface provider in model catalog
// 3. Use it:

const client = new OpenAI({
    apiKey: "PORTKEY_API_KEY",  // Portkey API key
    baseURL: PORTKEY_GATEWAY_URL
})

const response = await client.chat.completions.create({
    model: "@huggingface/meta-llama/Llama-3.2-3B-Instruct",
    messages: [{ role: "user", content: "Hello!" }]
})

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

```sh cURL icon="square-terminal" theme={"system"}
# 1. Add @huggingface provider in model catalog
# 2. Use it:

curl https://api.portkey.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -d '{
    "model": "@huggingface/meta-llama/Llama-3.2-3B-Instruct",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
```

## Add Provider in Model Catalog

Before making requests, add Hugging Face to your Model Catalog:

1. Go to [**Model Catalog → Add Provider**](https://app.portkey.ai/model-catalog/providers)
2. Select **Hugging Face**
3. Enter your [Hugging Face access token](https://huggingface.co/settings/tokens)
4. (Optional) Add a **Custom Host** if using a dedicated Hugging Face Inference Endpoint (e.g., `https://your-custom-url/v1`)
5. Name your provider (e.g., `huggingface`)

> [!NOTE]
>
> If you have a dedicated server hosted on Hugging Face, enter your dedicated endpoint URL in the **Custom Host** field during provider setup. This allows you to route requests to your private Hugging Face deployment.

> [card] [Complete Setup Guide](https://docs.portkey.ai/docs/product/model-catalog.md)
>
> See all setup options and detailed configuration instructions

***

## Supported Models

Hugging Face provides access to thousands of text generation models through their Inference endpoints, including:

* Meta Llama 3.2, Llama 3.1, Llama 3
* Mistral, Mixtral
* Qwen 2.5
* Phi-3
* Gemma, Gemma 2
* And thousands more!

Browse the complete catalog at [Hugging Face Models](https://huggingface.co/models?pipeline_tag=text-generation).

***

## Next Steps

> [card] [Gateway Configs](https://docs.portkey.ai/docs/product/ai-gateway.md)
>
> Add fallbacks, load balancing, and more

> [card] [Observability](https://docs.portkey.ai/docs/product/observability.md)
>
> Monitor and trace your Hugging Face requests

> [card] [Prompt Library](https://docs.portkey.ai/docs/product/prompt-engineering-studio.md)
>
> Manage and version your prompts

> [card] [Metadata](https://docs.portkey.ai/docs/product/observability/metadata.md)
>
> Add custom metadata to requests

For complete SDK documentation:

> [card] [SDK Reference](https://docs.portkey.ai/docs/api-reference/sdk/list.md)
>
> Complete Portkey SDK documentation

***

> [card] [Portkey is now PRISMA AIRS AI Gateway. See it in action.](https://www.paloaltonetworks.in/ai-security/ai-gateway?utm_source=portkey\&utm_medium=referral\&utm_campaign=prisma_airs\&utm_content=docs_nav#contact)
>
> Contact Us


## Related topics

- [Google Vertex AI](https://docs.portkey.ai/docs/integrations/llms/vertex-ai.md)
- [December](https://docs.portkey.ai/docs/changelog/2024/dec.md)
- [4. Advanced Strategies for Performance Improvement](https://docs.portkey.ai/docs/guides/whitepapers/optimizing-llm-costs/advanced-strategies.md)
- [How to Run Structured Output Evals at Scale](https://docs.portkey.ai/docs/guides/use-cases/run-batch-evals.md)
- [June](https://docs.portkey.ai/docs/changelog/2025/june.md)


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