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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-3.3-70B-Instruct-Turbo',
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-3.3-70B-Instruct-Turbo",
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}")
-
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Product Detail
Meta Llama 3.3 70B Instruct Turbo: Unleash Advanced AI Capabilities
Introducing Meta Llama 3.3 70B Instruct Turbo, a cutting-edge large language model engineered by Meta Platforms, Inc. This highly optimized LLM is designed to deliver exceptional performance in text generation and complex instruction-following tasks. Leveraging advanced AI techniques, it provides high-quality outputs with remarkable inference speeds, all while prioritizing safety and flexibility.
✨ Basic Information
- • Model Name: Meta Llama 3.3 70B Instruct Turbo
- • Developer/Creator: Meta Platforms, Inc.
- • Release Date: December 6, 2024
- • Version: 1.0
- • Model Type: Large Language Model (LLM)
🚀 Key Features
-
⚡
Optimized Performance: Utilizes FP8 quantization for significantly faster inference speeds with only a minor trade-off in accuracy, ensuring efficiency for demanding applications.
-
📖
Large Context Window: Supports an extensive context length, allowing for more comprehensive interactions and highly detailed, nuanced responses.
-
🗣️
Instruction Tuning: Specifically tuned for instruction-following tasks, making it ideal for conversational AI, task-oriented agents, and other interactive applications.
-
🏆
State-of-the-Art Benchmarks: Achieves top performance across a variety of benchmarks, including conversational tasks, language translation, and diverse text generation scenarios.
-
🛡️
Safety and Mitigation: Designed with a strong focus on responsible AI deployment, actively mitigating risks such as bias, toxicity, and misinformation in generated content.
💡 Intended Use
Meta Llama 3.3 70B Instruct Turbo is purpose-built for developers and researchers aiming to integrate advanced natural language processing capabilities into their applications. This includes use cases such as sophisticated chatbots, intelligent virtual assistants, dynamic content creation tools, and innovative educational software.
🌐 Language Support
The model offers robust support for multiple languages, significantly enhancing its versatility and usability in global applications and diverse linguistic contexts.
Technical Deep Dive
⚙️ Architecture
Meta Llama 3.3 utilizes a highly optimized transformer architecture. This design, enhanced by techniques like FP8 quantization, enables the model to efficiently process vast amounts of text while consistently delivering high-quality outputs.
📊 Training Data Insights
The model was trained on a diverse dataset compiled from various publicly available texts, ensuring robust performance across a wide array of scenarios.
- • Data Source and Size: The training dataset encompasses a broad range of topics and genres, though specific sizes are not publicly disclosed.
- • Knowledge Cutoff: The model's knowledge base is current as of December 2023.
- • Diversity and Bias: The training data curation focused on minimizing biases and maximizing diversity in topics and styles, significantly contributing to the model's overall effectiveness and fairness.
📈 Performance Metrics & Comparisons
Meta Llama 3.3 70B Instruct Turbo consistently demonstrates strong performance metrics, showcasing its advancements over previous models.
| Benchmark | Llama 3.1 8B Instruct | Llama 3.1 70B Instruct | Llama 3.3 70B Instruct | Llama 3.1 405B Instruct |
|---|---|---|---|---|
| MMLU (CoT) | 73.0 | 86.0 | 86.0 | 88.6 |
| MMLU Pro (CoT) | 48.3 | 66.4 | 68.9 | 73.3 |
| IFEval | 80.4 | 87.5 | 92.1 | 88.6 |
| GPQA Diamond (CoT) | 31.8 | 48.0 | 50.5 | 49.0 |
| HumanEval | 72.6 | 80.5 | 88.4 | 89.0 |
| MBPP EvalPlus (base) | 72.8 | 86.0 | 87.6 | 88.6 |
| MATH (CoT) | 51.9 | 68.0 | 77.0 | 73.8 |
| BFCL v2 | 65.4 | 77.5 | 77.3 | 81.1 |
| MGSM | 68.9 | 86.9 | 91.1 | 91.6 |
Usage & Integration
💻 Code Samples
The Meta Llama 3.3 70B Instruct Turbo model is readily available on the AI/ML API platform. Integrate it into your projects with ease.
import openai
client = openai.OpenAI(
base_url = "https://ai.cc/api/v1",
api_key = "YOUR_API_KEY",
)
chat_completion = client.chat.completions.create(
model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
messages=[
{"role": "user", "content": "Hello, how are you?"},
],
)
print(chat_completion.choices[0].message.content)
📄 API Documentation
For comprehensive integration guides and technical specifications, refer to the detailed API Documentation.
Ethical AI & Licensing
🤝 Ethical Guidelines
Meta places a strong emphasis on ethical considerations in AI development. This includes promoting transparency regarding the model's capabilities and limitations. We strongly encourage responsible usage to prevent misuse or harmful applications of generated content.
📜 Licensing Information
The Meta Llama 3.3 models are available under a community license. This license grants both research and commercial usage rights, while ensuring strict compliance with ethical standards and creator rights.
Ready to harness the power of Meta Llama 3.3 70B Instruct Turbo?
Get Meta Llama 3.3 70B Instruct Turbo API Here!❓ Frequently Asked Questions (FAQ)
Q1: What are the primary improvements in Meta Llama 3.3 70B Instruct Turbo?
A1: Key improvements include significantly faster inference speeds due to FP8 quantization, an enhanced large context window, and superior performance across various benchmarks for instruction-following and text generation tasks.
Q2: What is FP8 quantization and how does it benefit the model?
A2: FP8 quantization is a technique that reduces the precision of the model's numerical operations to 8-bit floating point. This significantly accelerates inference speeds with only a minimal trade-off in accuracy, making the model more efficient for deployment.
Q3: Can Meta Llama 3.3 70B Instruct Turbo be used for commercial applications?
A3: Yes, the model is available under a community license that permits both research and commercial usage, provided ethical standards and creator rights are upheld.
Q4: What is the knowledge cutoff date for this model?
A4: The model's knowledge is current as of December 2023, meaning it may not have information on events or developments that occurred after this date.
Q5: How can I access the API for Meta Llama 3.3 70B Instruct Turbo?
A5: You can access the API by signing up on the AI/ML API platform. Detailed documentation is also available to guide your integration.
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