Inference Providers documentation

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Together

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Supported tasks

Chat Completion (LLM)

Find out more about Chat Completion (LLM) here.

from huggingface_hub import InferenceClient

client = InferenceClient(
    provider="together",
    api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxx",
)

completion = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-R1",
    messages=[
        {
            "role": "user",
            "content": "What is the capital of France?"
        }
    ],
    max_tokens=500,
)

print(completion.choices[0].message)

Chat Completion (VLM)

Find out more about Chat Completion (VLM) here.

from huggingface_hub import InferenceClient

client = InferenceClient(
    provider="together",
    api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxx",
)

completion = client.chat.completions.create(
    model="meta-llama/Llama-4-Scout-17B-16E-Instruct",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Describe this image in one sentence."
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
                    }
                }
            ]
        }
    ],
    max_tokens=500,
)

print(completion.choices[0].message)

Text Generation

Find out more about Text Generation here.

from huggingface_hub import InferenceClient

client = InferenceClient(
    provider="together",
    api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxx",
)

completion = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-R1",
    messages="\"Can you please let us know more details about your \"",
    max_tokens=500,
)

print(completion.choices[0].message)

Text To Image

Find out more about Text To Image here.

from huggingface_hub import InferenceClient

client = InferenceClient(
    provider="together",
    api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxx",
)

# output is a PIL.Image object
image = client.text_to_image(
    "Astronaut riding a horse",
    model="black-forest-labs/FLUX.1-dev",
)
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