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Use Hanzo AI with Hugging Face

Access Hugging Face models and use the HF Inference API through the Hanzo AI API. Also use Hanzo AI models with HuggingFace Hub tooling.

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InferenceClient via Hanzopython
pip install huggingface_hub
 
from huggingface_hub import InferenceClient
 
client = InferenceClient(
    base_url="https://api.hanzo.ai/v1",
    api_key="your-hanzo-api-key",
)
 
output = client.chat.completions.create(
    model="meta-llama/llama-4-scout",
    messages=[{"role": "user", "content": "Hello!"}],
)
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hf CLI with Hanzo endpoint

python

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hf CLI with Hanzo endpointpython
# Use hf for model downloads, Hanzo for inference
hf download meta-llama/Llama-4-Scout-17B-16E-Instruct
 
# Then serve via Hanzo API
from openai import OpenAI
client = OpenAI(
    base_url="https://api.hanzo.ai/v1",
    api_key="your-hanzo-api-key",
)

JS InferenceClient

typescript

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JS InferenceClienttypescript
import { InferenceClient } from "@huggingface/inference";
 
const client = new InferenceClient("your-hanzo-api-key");
 
const chatCompletion = await client.chatCompletion({
  model: "meta-llama/llama-4-scout",
  messages: [{ role: "user", content: "Hello!" }],
  provider: "hanzo",
  endpointUrl: "https://api.hanzo.ai/v1",
});

cURL inference

bash

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cURL inferencebash
curl https://api.hanzo.ai/v1/chat/completions \
  -H "Authorization: Bearer $HANZO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"meta-llama/llama-4-maverick","messages":[{"role":"user","content":"Hi"}]}'

Created by Hugging Face

License: Apache-2.0 · View source on GitHub →

Hanzo AI is OpenAI-compatible, so existing Hugging Face code works with zero refactoring. We deeply appreciate the Hugging Face team for building and maintaining this open-source project.

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