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HuggingFace

HuggingFace ↗ helps users build, deploy and train machine learning models.

Endpoint

https://gateway.ai.cloudflare.com/v1/{account_id}/{gateway_id}/huggingface

URL structure

When making requests to HuggingFace Inference API, replace https://api-inference.huggingface.co/models/ in the URL you’re currently using with https://gateway.ai.cloudflare.com/v1/{account_id}/{gateway_id}/huggingface. Note that the model you’re trying to access should come right after, for example https://gateway.ai.cloudflare.com/v1/{account_id}/{gateway_id}/huggingface/bigcode/starcoder.

Prerequisites

When making requests to HuggingFace, ensure you have the following:

  • Your AI Gateway Account ID.
  • Your AI Gateway gateway name.
  • An active HuggingFace API token.
  • The name of the HuggingFace model you want to use.

Examples

cURL

Request
curl https://gateway.ai.cloudflare.com/v1/{account_id}/{gateway_id}/huggingface/bigcode/starcoder \
  --header 'Authorization: Bearer {hf_api_token}' \
  --header 'Content-Type: application/json' \
  --data '{
    "inputs": "console.log"
}'

Use HuggingFace.js library with JavaScript

If you are using the HuggingFace.js library, you can set your inference endpoint like this:

JavaScript
import { HfInferenceEndpoint } from "@huggingface/inference";


const accountId = "{account_id}";
const gatewayId = "{gateway_id}";
const model = "gpt2";
const baseURL = `https://gateway.ai.cloudflare.com/v1/${accountId}/${gatewayId}/huggingface/${model}`;
const apiToken = env.HF_API_TOKEN;


const hf = new HfInferenceEndpoint(baseURL, apiToken);