diff --git a/docs/inference-providers/index.md b/docs/inference-providers/index.md
index 380d2c894..4cec406b4 100644
--- a/docs/inference-providers/index.md
+++ b/docs/inference-providers/index.md
@@ -95,10 +95,11 @@ curl https://router.huggingface.co/novita/v3/openai/chat/completions \
 In Python, you can use the `requests` library to make raw requests to the API:
 
 ```python
+import os
 import requests
 
 API_URL = "https://router.huggingface.co/novita/v3/openai/chat/completions"
-headers = {"Authorization": "Bearer hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"}
+headers = {"Authorization": f"Bearer {os.environ['HF_TOKEN']}"}
 payload = {
     "messages": [
         {
@@ -116,11 +117,12 @@ print(response.json()["choices"][0]["message"])
 For convenience, the Python library `huggingface_hub` provides an [`InferenceClient`](https://huggingface.co/docs/huggingface_hub/guides/inference) that handles inference for you. Make sure to install it with `pip install huggingface_hub`.
 
 ```python
+import os
 from huggingface_hub import InferenceClient
 
 client = InferenceClient(
     provider="novita",
-    api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxx",
+    api_key=os.environ["HF_TOKEN"],
 )
 
 completion = client.chat.completions.create(
@@ -149,7 +151,7 @@ const response = await fetch(
     {
         method: "POST",
         headers: {
-            Authorization: `Bearer hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx`,
+            Authorization: `Bearer ${process.env.HF_TOKEN}`,
             "Content-Type": "application/json",
         },
         body: JSON.stringify({
@@ -173,7 +175,7 @@ For convenience, the JS library `@huggingface/inference` provides an [`Inference
 ```js
 import { InferenceClient } from "@huggingface/inference";
 
-const client = new InferenceClient("hf_xxxxxxxxxxxxxxxxxxxxxxxx");
+const client = new InferenceClient(process.env.HF_TOKEN);
 
 const chatCompletion = await client.chatCompletion({
     provider: "novita",