Enterprise Plans
AI Application Development
AI Translator API
AI SEO/GEO Service
Web Scraping Service
Log in
const { OpenAI } = require('openai');
const api = new OpenAI({
baseURL: 'https://api.ai.cc/v1',
apiKey: '',
});
const main = async () => {
const result = await api.chat.completions.create({
model: 'meta-llama/Llama-3-8b-chat-hf',
messages: [
{
role: 'system',
content: 'You are an AI assistant who knows everything.',
},
{
role: 'user',
content: 'Tell me, why is the sky blue?'
}
],
});
const message = result.choices[0].message.content;
console.log(`Assistant: ${message}`);
};
main();
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.ai.cc/v1",
api_key="",
)
response = client.chat.completions.create(
model="meta-llama/Llama-3-8b-chat-hf",
messages=[
{
"role": "system",
"content": "You are an AI assistant who knows everything.",
},
{
"role": "user",
"content": "Tell me, why is the sky blue?"
},
],
)
message = response.choices[0].message.content
print(f"Assistant: {message}")
-
AI Playground
Test all API models in the sandbox environment before you integrate.
We provide more than 300 models to integrate into your app.
Product Detail
✨ LLama-3 Chat (8B): Optimized Conversational AI
Developed by Meta and released on April 18, 2024, LLama-3 Chat (8B) is a cutting-edge Large Language Model (LLM) expertly designed for natural and coherent dialogue. This 8-billion parameter model is specifically tuned for conversational AI and instruction-following tasks, making it an ideal choice for chatbots, virtual assistants, and customer support systems.
Its robust architecture ensures high-quality outputs and efficient processing, offering a balanced solution for developers and researchers aiming to implement advanced conversational capabilities.
Key Capabilities
- ✅ 8 Billion Parameters: Achieves an optimal balance between powerful performance and computational efficiency.
- 💬 Instruction-Tuned: Precisely optimized to understand and accurately follow user instructions, generating contextually relevant responses.
- ⚡ Grouped-Query Attention (GQA): Significantly enhances inference speed and improves overall scalability for demanding applications.
- 📚 High Context Length: Supports inputs of up to 8,192 tokens, enabling extensive and complex dialogue management.
- 🌐 Multilingual Capabilities: Designed to process and generate text effectively across multiple languages, ideal for global applications.
⚙️ Technical Specifications
Architecture
LLama-3 Chat (8B) employs an advanced transformer architecture, further optimized with Grouped-Query Attention (GQA). This sophisticated design facilitates the efficient processing of large text volumes while consistently delivering high-quality outputs. Its architecture is particularly adept at managing the long context inputs frequently encountered in complex conversational scenarios.
Training Data
The model was rigorously trained on an extensive dataset comprising over 15 trillion tokens sourced from publicly available information. This vast dataset ensures a broad and deep understanding of language and context.
- • Data Source & Size: The training corpus includes diverse text from books, websites, and various media, significantly enhancing the model's robustness across a wide range of topics and styles.
- • Knowledge Cutoff: The model's knowledge base is current as of March 2023.
- • Diversity & Bias: Meta meticulously curated the training data to minimize potential biases while maximizing topic and style diversity, contributing to the model's overall effectiveness and fairness.
Performance Metrics
LLama-3 Chat (8B) consistently demonstrates strong performance metrics across various benchmarks.
Comparative performance benchmarks for LLama-3 Chat (8B).
💡 Usage & Ethical Guidelines
Code Samples & API Access
The LLama-3 Chat (8B) model is readily available on the AI/ML API platform under the identifier "LLama-3 Chat (8B)".
Code samples for integrating LLama-3 Chat (8B) via API typically involve a chat completion request. You would usually include your API key and define the model and message structure.
import requests
url = "YOUR_API_ENDPOINT/chat/completions"
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
data = {
"model": "meta-llama/Llama-3-8b-chat-hf",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is the capital of France?"}
]
}
response = requests.post(url, headers=headers, json=data)
print(response.json())
Get direct access to the LLama-3 Chat (8B) API here to start building your applications.
Ethical Considerations
Meta places a strong emphasis on ethical AI development. They advocate for transparency regarding the model's capabilities and inherent limitations. Users are encouraged to adhere to responsible usage guidelines to prevent any potential misuse or the generation of harmful content.
Licensing
LLama models, including LLama-3 Chat (8B), are distributed under an open-source license. This license permits both research and commercial usage, provided all ethical standards and compliance requirements are met.
❓ Frequently Asked Questions
Q1: What is LLama-3 Chat (8B) primarily designed for?
LLama-3 Chat (8B) is primarily optimized for conversational AI and instruction-following tasks, making it ideal for developing chatbots, virtual assistants, and customer support systems that require natural and coherent dialogue.
Q2: What is the context window size for LLama-3 Chat (8B)?
The model supports a high context length, allowing inputs of up to 8,192 tokens. This enables it to manage extensive and complex dialogues effectively.
Q3: Is LLama-3 Chat (8B) suitable for multilingual applications?
Yes, LLama-3 Chat (8B) possesses robust multilingual capabilities, allowing it to process and generate text in multiple languages, making it highly suitable for diverse global applications.
Q4: What is the knowledge cutoff date for LLama-3 Chat (8B)?
The model's knowledge is current as of March 2023, based on the extensive training data it was exposed to.
Q5: Is LLama-3 Chat (8B) available for commercial use?
Yes, LLama models, including the 8B chat version, are released under an open-source license that permits both research and commercial usage, provided ethical standards are maintained.
Learn how you can transformyour company with AICC APIs
