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Currently, we support the Chat Completion endpoint via the Hugging Face Python client. To get started, follow the steps below. Learn more on the Hugging Face website.
1

Install the Hugging Face Hub client

pip install huggingface_hub --upgrade
2

Create a new Hugging Face API key

Next, you’ll need to create a new Hugging Face API key. You’ll use this key to authenticate with Hugging Face and access the Cerebras provider.
  1. Go to hf.co/settings/tokens
  2. Click “New token”
  3. Give it a name and copy your API key
3

Make an API call

Here’s an example using InferenceClient to query Llama 3.3-70B on Cerebras.Be sure to replace "hf_your_api_key_here" with your actual API key.
from huggingface_hub import InferenceClient

client = InferenceClient(
    provider="cerebras",
    api_key="hf_your_api_key_here",
)

completion = client.chat.completions.create(
    model="meta-llama/Llama-3.3-70B-Instruct",
    messages=[
        {"role": "user", "content": "What is the capital of France?"}
    ],
    max_tokens=500,
)

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

​
FAQ

Since inference is routed through Hugging Face’s proxy, users may experience slightly higher latency compared to calling Cerebras Cloud directly.
The official Hugging Face inference example uses a multimodal input call, which is not currently supported by Cerebras. To avoid this error, use the code provided in Step 3 of the tutorial above.
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