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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-3-70b-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-3-70b-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}")
-
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Product Detail
🚀 Llama 3 70B Instruct: A New Era in Language AI
Model Name: Llama 3 70B Instruct
Developer/Creator: Meta
Release Date: April 18, 2024
Version: 3
Model Type: Large Language Model (LLM)
Llama 3 70B Instruct represents a significant advancement in large language models. Designed for sophisticated assistant-like chat and various natural language generation tasks, this state-of-the-art model from Meta offers substantial improvements over its predecessor, Llama 2, particularly in areas like reasoning, code generation, and instruction following.
✨ Key Features Setting Llama 3 Apart:
- Advanced Reasoning and Code Generation: Enhanced capabilities for complex problem-solving and programming tasks.
- Improved Instruction Following and Alignment: More accurately interprets and executes user instructions.
- Reduced False Refusal Rates: Less likely to incorrectly decline valid requests.
- Increased Diversity in Model Responses: Generates a wider range of creative and relevant outputs.
- Enhanced Steerable Outputs: Offers greater control over the nature and style of generated content.
🎯 Intended Use & Language Support:
The Llama 3 70B Instruct model is primarily developed for commercial and research applications in English. Its core focus lies in powering assistant-like chat systems and various natural language generation tasks.
While optimized for English, developers have the flexibility to fine-tune the model for other languages. This must be done in strict compliance with the Llama 3 Community License and its Acceptable Use Policy.
⚙️ Technical Deep Dive
Architecture Overview:
- Decoder-only Transformer: A robust architecture optimized for generative tasks.
- 70 Billion Parameters: A massive parameter count enabling complex understanding and generation.
- Grouped Query Attention (GQA): Significantly improves inference efficiency, crucial for large models.
- 128K Token Vocabulary: Facilitates more efficient and nuanced language encoding.
- 8,192 Token Context Window: Allows the model to process and maintain context over longer conversations and documents.
Training Data Insights:
- Trained on an unprecedented up to 15 trillion tokens.
- Remarkable performance improvements were observed even after training on two orders of magnitude more data than the Chinchilla-optimal amount.
- Utilizes a diverse dataset specifically curated to enhance overall model performance and mitigate potential biases.
📊 Performance Metrics:
MMLU Score: 0.82
Quality Index Across Evaluations: 62
Output Speed: 54.3 tokens per second
Time to First Token (TTFT): 0.44 seconds
Comparison to Other Models:
- Llama 3 70B Instruct sets a new state-of-the-art benchmark for LLM models at the 70B parameter scale.
- Human annotator evaluations confirm that it outperforms competing models of comparable size in real-world scenarios, demonstrating superior utility and performance.
💡 Usage Guidelines
Code Samples:
# Example Python usage (conceptual)
from llama3_api import Llama3Client
client = Llama3Client(model="meta-llama/Llama-3-70b-chat-hf")
response = client.chat_completion(prompt="Hello, what can you do?")
print(response.choices[0].message.content)
Note: This is a placeholder for actual API code snippets. Refer to official Meta Llama 3 documentation for precise integration examples.
✅ Ethical Guidelines:
Llama 3 70B Instruct is built with a strong commitment to ethical considerations, upholding core principles such as:
- Promoting Openness, Inclusivity, and Helpfulness: Designed to assist a broad user base.
- Respecting User Dignity and Autonomy: Ensures user interactions are respectful and empowering.
- Avoiding Unnecessary Judgment or Normativity: Strives for neutrality and impartiality in responses.
- Following a Responsible Use Guide: Comprehensive guidelines are in place to mitigate potential misuse and critical risks.
📄 Licensing Information:
License Type: Llama 3 Community License
- The license permits both commercial and research use of the model.
- Usage is strictly prohibited in ways that violate applicable laws or regulations.
- For complete details, please refer to the official Llama 3 Community License and Acceptable Use Policy.
❓ Frequently Asked Questions (FAQ)
Q1: What is Llama 3 70B Instruct primarily designed for?
A1: It's primarily designed for assistant-like chat applications and various natural language generation tasks, intended for commercial and research use in English.
Q2: How does Llama 3 70B Instruct compare to its predecessor, Llama 2?
A2: Llama 3 70B Instruct offers significant improvements in reasoning, code generation, instruction following, reduced false refusal rates, and increased diversity in responses.
Q3: Can Llama 3 70B Instruct be used for languages other than English?
A3: While primarily designed for English, developers can fine-tune the model for other languages, provided they comply with the Llama 3 Community License and Acceptable Use Policy.
Q4: What are the ethical considerations for using Llama 3 70B Instruct?
A4: It adheres to strict ethical guidelines, promoting openness, inclusivity, helpfulness, respecting user dignity, avoiding unnecessary judgment, and following a responsible use guide to mitigate risks.
Q5: Is Llama 3 70B Instruct suitable for commercial applications?
A5: Yes, the Llama 3 Community License explicitly allows for commercial use, alongside research use, provided all terms and conditions of the license are followed.
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