# Source: https://deepinfra.com/docs/getting-started

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[Models](/models)

[Automatic Speech Recognition](/models/automatic-speech-
recognition)[Embeddings](/models/embeddings)[Reranker](/models/reranker)[Text
Generation](/models/text-generation)[Text To Image](/models/text-to-
image)[Text To Speech](/models/text-to-speech)[Text To Video](/models/text-to-
video)[Zero Shot Image Classification](/models/zero-shot-image-classification)

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  1. [Getting Started](/docs)

     1. Quick Start Guide

     2. [Available Models](/docs/models)

     3. [Running Inference](/docs/inference)

     4. [Data Privacy & Security](/docs/data)

  2. [API Reference](/docs/api-reference)

     1. [OpenAI-Compatible API](/docs/openai_api)

     2. [DeepInfra Native API](/docs/deep_infra_api)

     3. [Rate Limits](/docs/advanced/rate-limits)

     4. [Webhooks](/docs/advanced/webhooks)

     5. [Authentication & Tokens](/docs/advanced/scoped_jwt)

  3. [Model Features](/docs/model-features)

     1. [Function Calling](/docs/advanced/function_calling)

     2. [JSON Mode](/docs/advanced/json_mode)

     3. [Multimodal Models](/docs/advanced/multimodal)

     4. [Log Probabilities](/docs/advanced/log_probs)

     5. [Max Output Tokens](/docs/advanced/max_tokens_limit)

  4. [GPU Instances](/docs/gpu-instances)

     1. [Containers](/docs/gpu-instances/containers)

  5. [Custom Deployments](/docs/custom-deployments)

     1. [Custom LLMs](/docs/advanced/custom_llms)

     2. [LoRA Adapter Models](/docs/advanced/lora)

     3. [LoRA Image Adapters](/docs/advanced/lora_text_to_image)

  6. [Integrations](/docs/integrations)

     1. [LangChain](/docs/advanced/langchain)

     2. [LlamaIndex](/docs/advanced/llama-index)

     3. [AI SDK](/docs/advanced/aisdk)

     4. [AutoGen](/docs/advanced/autogen)

     5. [Okta SSO](/docs/advanced/okta)

  7. [Tutorials & Examples](/docs/tutorials)

     1. [Stable Diffusion (Text to Image)](/docs/tutorials/stable-diffusion)

     2. [Whisper (Speech to Text)](/docs/tutorials/whisper)

     3. [Deprecated Models](/docs/advanced/deprecated)

  8. [Miscellaneous](/docs/misc)

     1. [Data Subprocessors](/docs/misc/subprocessors)

Documentation

  1. [Getting Started](/docs)

     1. Quick Start Guide

     2. [Available Models](/docs/models)

     3. [Running Inference](/docs/inference)

     4. [Data Privacy & Security](/docs/data)

  2. [API Reference](/docs/api-reference)

     1. [OpenAI-Compatible API](/docs/openai_api)

     2. [DeepInfra Native API](/docs/deep_infra_api)

     3. [Rate Limits](/docs/advanced/rate-limits)

     4. [Webhooks](/docs/advanced/webhooks)

     5. [Authentication & Tokens](/docs/advanced/scoped_jwt)

  3. [Model Features](/docs/model-features)

     1. [Function Calling](/docs/advanced/function_calling)

     2. [JSON Mode](/docs/advanced/json_mode)

     3. [Multimodal Models](/docs/advanced/multimodal)

     4. [Log Probabilities](/docs/advanced/log_probs)

     5. [Max Output Tokens](/docs/advanced/max_tokens_limit)

  4. [GPU Instances](/docs/gpu-instances)

     1. [Containers](/docs/gpu-instances/containers)

  5. [Custom Deployments](/docs/custom-deployments)

     1. [Custom LLMs](/docs/advanced/custom_llms)

     2. [LoRA Adapter Models](/docs/advanced/lora)

     3. [LoRA Image Adapters](/docs/advanced/lora_text_to_image)

  6. [Integrations](/docs/integrations)

     1. [LangChain](/docs/advanced/langchain)

     2. [LlamaIndex](/docs/advanced/llama-index)

     3. [AI SDK](/docs/advanced/aisdk)

     4. [AutoGen](/docs/advanced/autogen)

     5. [Okta SSO](/docs/advanced/okta)

  7. [Tutorials & Examples](/docs/tutorials)

     1. [Stable Diffusion (Text to Image)](/docs/tutorials/stable-diffusion)

     2. [Whisper (Speech to Text)](/docs/tutorials/whisper)

     3. [Deprecated Models](/docs/advanced/deprecated)

  8. [Miscellaneous](/docs/misc)

     1. [Data Subprocessors](/docs/misc/subprocessors)

# Getting Started

You don't need to install anything to do your first inference. You only need
[your access token](/dash/api_keys).

Go to the API section on any model's page. Grab one of the examples. If you
are logged in your access token will be prefilled for you.

You can try one of the examples from [meta-llama/Meta-
Llama-3-8B-Instruct](/meta-llama/Meta-Llama-3-8B-Instruct/api)

    
    
    curl "https://api.deepinfra.com/v1/openai/chat/completions" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer $DEEPINFRA_TOKEN" \
      -d '{
          "model": "meta-llama/Meta-Llama-3-8B-Instruct",
          "messages": [
            {
              "role": "user",
              "content": "Hello!"
            }
          ]
        }'
    
    
    copy

and it will respond with something like

    
    
    {
        "id": "chatcmpl-guMTxWgpFf",
        "object": "chat.completion",
        "created": 1694623155,
        "model": "meta-llama/Meta-Llama-3-8B-Instruct",
        "choices": [
            {
                "index": 0,
                "message": {
                    "role": "assistant",
                    "content": " Hello! It's nice to meet you. Is there something I can help you with or would you like to chat for a bit?"
                },
                "finish_reason": "stop"
            }
        ],
        "usage": {
            "prompt_tokens": 15,
            "completion_tokens": 16,
            "total_tokens": 31,
            "estimated_cost": 0.0000268
        }
    }
    
    
    copy

This example uses the [OpenAI Chat Completions API](/docs/openai_api) which we
strongly recommend because it is the most convenient to use when dealing with
LLMs. You can also use it with the official JavaScript/Node.js and Python
libraries and they will work out of the box.

If you want to dip your toes a little more in the AI world you can try the
following example

    
    
    curl "https://api.deepinfra.com/v1/inference/meta-llama/Meta-Llama-3-8B-Instruct" \
       -H "Content-Type: application/json" \
       -H "Authorization: Bearer $DEEPINFRA_TOKEN" \
       -d '{
         "input": "<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\nHello!<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
         "stop": [
           "<|eot_id|>"
         ]
       }'
    
    
    copy

It is using DeepInfra's API and it require advanced knowledge of how the model
works, which in turn gives you more flexiblity. You can read specifics about
each model in its API section including stop words, streaming and more.

You will get a response similar to the previous example

    
    
    {
        "request_id": "RWZDRhS5kdoM1XWwXLEshynO",
        "inference_status": {
            "status": "succeeded",
            "runtime_ms": 243,
            "cost": 0.0000436,
            "tokens_input": 12,
            "tokens_generated": 25
        },
        "results": [
            {
                "generated_text": "Hello! It's nice to meet you. Is there something I can help you with or would you like to chat for a bit?"
            }
        ],
        "num_tokens": 25,
        "num_input_tokens":12
    }
    
    
    copy

[Getting Started](/docs)[Available Models](/docs/models)

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