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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: 'Qwen/Qwen2.5-7B-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="Qwen/Qwen2.5-7B-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
✨ Introducing Qwen 2.5 7B Instruct Turbo: A Breakthrough in LLM Technology
The Qwen 2.5 7B Instruct Turbo model represents a significant leap forward in large language model development by Alibaba Group. Released on September 18, 2024, this Version 2.5 text-based model is engineered to provide sophisticated text understanding and generation capabilities, making it an invaluable tool for a wide array of applications.
💡 Key Capabilities & Features
This cutting-edge model is designed to excel in various demanding tasks, offering unparalleled performance:
- ✅ Extended Context Window: Supports long-context inputs up to 131,072 tokens, enabling deeper understanding of complex information.
- ✅ Robust Output Generation: Capable of generating extensive outputs, reaching up to 8,192 tokens.
- ✅ Enhanced Instruction Following: Significantly improved adherence to specific instructions for precise task execution.
- ✅ Multilingual Proficiency: Offers comprehensive support for over 29 languages, including English, Chinese, Spanish, and many others, facilitating global applications.
- ✅ Superior Performance: Demonstrates marked improvements in coding and mathematical problem-solving compared to its predecessors.
🚀 Intended Applications
The Qwen 2.5 7B Instruct Turbo model is ideal for developers, researchers, and businesses aiming to integrate advanced NLP into their systems. Key application areas include:
- ⭐ Automated Content Creation: Generating high-quality articles, reports, and marketing copy efficiently.
- ⭐ Advanced Coding Assistance: From generating code snippets to intelligent debugging and refactoring.
- ⭐ Intelligent Chatbots & Virtual Assistants: Powering conversational AI with sophisticated understanding and response generation.
🔧 Technical Deep Dive: Qwen 2.5 Architecture
Understanding the core mechanics of Qwen 2.5 reveals its robust engineering:
- 🌀 Advanced Transformer Architecture: Built upon a refined Transformer framework, incorporating innovations such as RoPE (Rotary Positional Embedding), SwiGLU activation functions, RMSNorm normalization, and Attention QKV bias for superior processing.
- 🧩 Layer Configuration: Comprises 28 layers and 28 attention heads, optimized for efficient query processing and deep semantic understanding.
- 💾 Expansive Training Dataset: Trained on an immense dataset exceeding 18 trillion tokens. This diverse collection includes books, websites, and programming repositories, ensuring broad knowledge and adaptability.
- 🕜 Knowledge Cutoff: The model's knowledge base is current as of October 2024.
🛡 Diversity & Bias: Alibaba Group has made considerable efforts to ensure the training data is diverse, aiming to mitigate biases. However, as with all AI models, some inherent biases from the training data may still be present.
📊 Performance Highlights
Qwen 2.5 7B Instruct Turbo delivers exceptional performance across key metrics:
- ⭐ Accuracy: Achieved an impressive MMLU score of approximately 74.2, demonstrating robust language understanding.
- ⭐ Speed: Optimized for fast inference, making it highly suitable for real-time applications requiring rapid responses.
- ⭐ Robustness: Exhibits remarkable adaptability to diverse inputs and consistently strong performance, even with complex or ambiguous queries.
💻 Comparing Qwen 2.5 to Peers
In competitive benchmarks, Qwen 2.5 7B Instruct Turbo stands out, showcasing its advanced capabilities. For a visual comparison and detailed insights into how it performs against other leading models, refer to the comparative analysis provided below:
📜 Usage & Ethical Guidelines
Developers can integrate Qwen 2.5 into their projects using straightforward API calls. Example code snippets for various tasks, such as chat completion, are readily available to facilitate quick deployment.
🛡 Ethical AI Commitment: The development of Qwen 2.5 strictly adheres to ethical AI principles, emphasizing transparency, fairness, and accountability. Users are strongly encouraged to align with these guidelines when deploying the model to ensure responsible and beneficial applications.
📃 Licensing Information
The Qwen 2.5 models are made available under the Apache 2.0 License, permitting both commercial and non-commercial use, offering broad flexibility for innovation.
❓ Frequently Asked Questions (FAQ)
Q: What is Qwen 2.5 7B Instruct Turbo?
A: Qwen 2.5 7B Instruct Turbo is a state-of-the-art large language model developed by Alibaba Group, designed for advanced text understanding and generation, with enhanced capabilities in coding, mathematics, and instruction following.
Q: What are the main features of Qwen 2.5?
A: Key features include support for long contexts (up to 131,072 tokens), generating outputs up to 8,192 tokens, improved instruction adherence, and multilingual support for over 29 languages.
Q: How does Qwen 2.5 perform in technical tasks like coding?
A: Qwen 2.5 shows significant improvements in coding and mathematical problem-solving compared to previous versions, making it highly effective for software development and technical research.
Q: What is the licensing model for Qwen 2.5?
A: The Qwen 2.5 models are available under the Apache 2.0 License, allowing for both commercial and non-commercial deployment without restrictions.
Q: Is Qwen 2.5 suitable for real-time applications?
A: Yes, Qwen 2.5 is optimized for fast inference, ensuring quick response times that are crucial for real-time applications such as chatbots and virtual assistants.
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