Content-Type: application/json
Cache-Control: no-cache

    "prompt": "Tell me about FIFA"

import urllib.request, json

    url = ""

    hdr ={
    # Request headers
    'Content-Type': 'application/json',
    'Cache-Control': 'no-cache',

    # Request body
    data =  
    data = json.dumps(data)
    req = urllib.request.Request(url, headers=hdr, data = bytes(data.encode("utf-8")))

    req.get_method = lambda: 'POST'
    response = urllib.request.urlopen(req)
    except Exception as e:
// Request body
const body = {
    "prompt": "Tell me about FIFA"

fetch('', {
        method: 'POST',
        body: JSON.stringify(body),
        // Request headers
        headers: {
            'Content-Type': 'application/json',
            'Cache-Control': 'no-cache',}
    .then(response => {
    .catch(err => console.error(err));
curl -v -X POST "" -H "Content-Type: application/json" -H "Cache-Control: no-cache" --data-raw "{
    \"prompt\": \"Tell me about FIFA\"
import java.util.HashMap;
import java.util.Map;

public class HelloWorld {

  public static void main(String[] args) {
    try {
        String urlString = "";
        URL url = new URL(urlString);
        HttpURLConnection connection = (HttpURLConnection) url.openConnection();

        //Request headers
    connection.setRequestProperty("Content-Type", "application/json");
    connection.setRequestProperty("Cache-Control", "no-cache");

        // Request body
             "{ \"prompt\": \"Tell me about FIFA\" }".getBytes()
        int status = connection.getResponseCode();

        BufferedReader in = new BufferedReader(
            new InputStreamReader(connection.getInputStream())
        String inputLine;
        StringBuffer content = new StringBuffer();
        while ((inputLine = in.readLine()) != null) {

    } catch (Exception ex) {
      System.out.print("exception:" + ex.getMessage());
$url = "";
$curl = curl_init($url);

curl_setopt($curl, CURLOPT_CUSTOMREQUEST, "POST");
curl_setopt($curl, CURLOPT_URL, $url);
curl_setopt($curl, CURLOPT_RETURNTRANSFER, true);

# Request headers
$headers = array(
    'Content-Type: application/json',
    'Cache-Control: no-cache',);
curl_setopt($curl, CURLOPT_HTTPHEADER, $headers);

# Request body
$request_body = '{
    "prompt": "Tell me about FIFA"
curl_setopt($curl, CURLOPT_POSTFIELDS, $request_body);

$resp = curl_exec($curl);
Llama 2 13B Chat API
  • API Documentation for Llama 2 13B Chat

    The Llama 2 13B Chat API is a powerful tool for integrating the Llama 2 13B Chat model into various applications. This API provides a seamless interface for developers to harness the capabilities of the model for AI applications through our Llama materials


    Llama 2 13B Chat represents a pinnacle in conversational AI, leveraging a Llama 2 13B Chat API and Llama 2 13B Chat AI model to deliver cutting-edge capabilities beyond the basic Llama 2 Chat model. With its 13 billion parameters, this AI model is part of the broader Llama Model series, known for its prowess in text-generation tasks across diverse AI applications. Built upon extensive datasets and designed as an open-source initiative, the Llama 2 13B Chat excels in creating contextually aware responses, suitable for large language models and machine-learning applications.

    The Llama 2 13B Chat API simplifies integration, enabling developers to harness its robust functionalities in creating sophisticated chat bots and enhancing user interactions. As an evolution from Llama 1, this base model extends capabilities, offering increased context length and refined AI capabilities. The Llama 2 13B Chat AI model utilizes advanced machine-learning techniques, drawing from comprehensive Llama materials, to ensure nuanced dialogue generation, fostering dynamic conversational experiences.

    Developers benefit from the Llama 2 13B Chat's adaptability in various AI applications, supporting innovative solutions across industries. Its implementation through open-source frameworks facilitates community collaboration and continuous improvement. Whether for customer service, virtual assistants, or creative content generation, the Llama 2 13B Chat stands out for its AI model sophistication and Code Llama Instruct capabilities, driving forward the next generation of AI-driven interactions. Developers can customize interactions through system prompts, ensuring tailored user experiences and efficient communication channels via email address integration for notifications and updates.

    The Llama 2 13B Chat model excels in chat completion, utilizing a broad context window and Input token optimization to generate fluid and contextually appropriate responses. Leveraging advancements from the Llama 2 70B model, it sets new standards in code generation and meta-llama applications, solidifying its position as a leader in AI innovation and text-generation technology. Developers can further enhance its capabilities through the use of a fine-tuned model, enabling them to achieve more precise and tailored responses to user prompts and queries.

  • API Parameters

    The API POST takes the following parameters:


    string, required


    string, optional


    Integration and Implementation

    To use Llama 2 13B Chat, developers must send POST requests to the specified endpoint, including the appropriate headers and request body. The request body should contain text inputs, task parameters, and additional settings.

    Base URL

    POST /Get Data

    This endpoint generates text based on the prompts provided.

    • URL:
    • Method: POST
    • Headers:
      • Content-Type: application/json
      • Cache-Control: no-cache
      • Ocp-Apim-Subscription-Key: {subscription_key}
    • Body:


        "prompt": "Tell me about the FIFA"
  • Responses
    • HTTP Status Codes:
      • 200 OK: The request was successful, and the generated text is included in the response body.
      • 400 Bad Request: The request must be corrected or include some arguments.
      • 401 Unauthorized: The API key provided in the header is invalid.
      • 500 Internal Server Error: An error occurred on the server while processing the request.
    • Sample Response:


        "status": 200,
        "content-type": "application/json"
    Error Handling

    The Llama 2 13B Chat API features robust error-handling mechanisms to ensure seamless operation. Common status codes encountered include:

    • Error Field Contract:
      • code: An integer that indicates the HTTP status code (e.g., 400, 401, 500).
      • message: A clear and concise description of what the error is about.
      • traceId: A unique identifier that can be used to trace the request in case of issues.
    • AI Model: Refers to the underlying machine learning model used to interpret the text prompts and generate corresponding texts.
    • Changelog: Document detailing any updates, bug fixes, or improvements made to the API in each version.

    Use Case of Llama 2 13B Chat API

    • Customer Support Chatbots: Implementing Llama 2 13B Chat for customer service enhances interactions with contextually relevant output tokens and fine-tuned generative text models, ensuring accurate and helpful responses.
    • Educational Chat Assistants: Utilizing its auto-regressive language model, Llama 2 13B Chat API supports educational platforms by providing detailed explanations and interactive learning experiences. Educators can upload text files and interact through user messages, leveraging the API's capability to maintain a sufficient context size for comprehensive learning sessions.
    • Virtual Healthcare Providers: In healthcare, Llama 2 13B Chat API aids in patient consultations and medical information dissemination, leveraging its parameter language model for precise communication.
    • Programming Language Assistance: Llama 2 13B Chat assists developers by offering insights into coding queries and programming concepts, benefiting from its third-party integration capabilities and expertise in programming language.
    • Creative Writing Tools: Writers and content creators use Llama 2 13B Chat for generating ideas and refining narratives, benefiting from its generative AI capabilities and support for dialogue use cases. By inputting user_input directly into the model code, creators can refine their content seamlessly, ensuring a polished end user product ready for publication or distribution.
    • Financial Advisory Services: Llama 2 13B Chat API supports financial institutions by providing personalized advice and insights into complex financial scenarios, utilizing its reinforcement learning capabilities for decision-making processes.
    • Legal Consultation Platforms: Integrating Llama 2 13B Chat API into legal services enhances legal research and client interactions, leveraging its model size and meta Llama 3 features to handle intricate legal queries effectively.

    Advanced Features of the Llama 2 13B Chat API

    • Enhanced Security Measures: Llama 2 13B Chat API prioritizes security concerns by implementing robust encryption protocols and ensuring compliance with trade compliance laws to safeguard sensitive data.
    • Flexible Integration with GPU: Developers benefit from efficient processing capabilities by leveraging GPU devices, and optimizing performance for complex tasks and large-scale deployments.
    • Comprehensive Pretrained Models: Access to a diverse array of pre-trained models allows developers to choose the most suitable configurations for their applications, enhancing versatility and performance.
    • Interactive User Prompts: The Llama 2 13B Chat API supports user prompts to guide interactions, enabling intuitive and engaging dialogue flows tailored to user needs and preferences.
    • Advanced Python Code Integration: Developers can seamlessly integrate Python code within conversations, facilitating dynamic responses and expanding functionality beyond traditional text-based interactions.
    • Community Support and Resources: Leveraging the Llama-2: Open Foundation and Fine community, developers have access to extensive resources such as Stack Overflow support, a Responsible Use Guide, and a list of messages for best practices and troubleshooting guidance.

    Technical Specifications of the Llama 2 13B Chat API

    • Model Architecture: The Llama 2 13B Chat API is built on the Llama 2 13B Chat AI model, featuring 13 billion parameters optimized for natural language processing and text generation tasks.
    • Integration Protocols: Developers can access the API through standard HTTP protocols, facilitating seamless integration into existing systems and applications for handling inference requests.
    • GPU Acceleration: The API supports GPU acceleration to enhance computational efficiency, optimizing performance and reducing GPU hours required for intensive computations.
    • Input and Output Formats: Inputs are accepted in JSON format, ensuring compatibility with a wide range of programming languages and frameworks, while outputs consist of contextually appropriate responses generated by fine-tuned chat models.
    • Scalability and Performance: Designed for scalability, the Llama 2 13B Chat API can efficiently manage a maximum number of concurrent users and requests, maintaining low latency even during peak usage.
    • Security and Compliance: The Llama 2 13B Chat API adheres to security best practices and an Acceptable Use Policy, ensuring compliance with applicable laws and regulations to protect user data and privacy. This commitment extends across implementations using both smaller models and artificial intelligence, ensuring robust security measures are consistently applied regardless of model size or AI complexity.
    • Documentation and Support: Comprehensive API Reference documentation, available at the official developer portal, includes guidelines for reporting bugs, asking questions, and optimizing API usage, supporting developers through various following means such as forums and community support.

    What are the Benefits of Using Llama 2 13B Chat API

    • Advanced Conversational Capabilities: Leveraging a state-of-the-art AI model with 13 billion parameters, the API delivers highly accurate and contextually relevant responses, enhancing the quality of interactions across various applications.
    • Versatility in Applications: Suitable for diverse use cases such as customer support, virtual assistants, and creative content generation, the Llama 2 13B Chat API adapts to different domains with its robust text-generation capabilities.
    • Scalability and Performance: Designed for scalability, the API efficiently handles high volumes of requests, ensuring low latency and reliable performance even under heavy loads, supported by GPU acceleration for enhanced computational efficiency.
    • Ease of Integration: Developers benefit from straightforward HTTP integration and support for JSON input formats, enabling seamless integration into existing systems and workflows without extensive modifications.
    • Security and Compliance: Adhering to rigorous security standards and an Acceptable Use Policy, the Llama 2 13B Chat API ensures data privacy and compliance with applicable laws, mitigating risks associated with data handling and processing.
    • Customizable Notifications: Developers can configure notification settings to manage system messages and user interactions, ensuring effective communication and operational efficiency.
    • Documentation and Support: Access to comprehensive documentation, API reference guides, and community forums facilitates learning, troubleshooting, and optimization, empowering developers to maximize the API's capabilities effectively.
    • Attribution and Transparency: The API supports attribution notices and model cards, promoting transparency in AI system usage and facilitating compliance with ethical guidelines and sustainability programs.

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