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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: 'tiiuae/falcon-40b-instruct',
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="tiiuae/falcon-40b-instruct",
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 Falcon Instruct (40B): A Leap in Open-Source AI
The Falcon Instruct (40B) model, meticulously engineered by the Technology Innovation Institute (TII), represents a significant advancement in large language models. Built upon the robust Falcon-40B architecture, this 40-billion parameter model has been finely tuned using a diverse mix of the Baize dataset. Released under the widely accessible Apache 2.0 license, it ushers in a new era of high-performance and accessible open-source language modeling for developers and researchers worldwide.
🚀 Why Falcon Instruct (40B) Stands Out
Falcon Instruct (40B) is expertly designed for chat and instruction-based applications, leveraging the powerful Falcon-40B framework for reliability and efficiency.
Key Differentiators Include:
- Leading Open-Source Performance: It consistently ranks as the top open-source model, outperforming competitors like LLaMA and StableLM on the OpenLLM Leaderboard.
- Optimized Architecture: Incorporates innovations such as FlashAttention and multiquery attention mechanisms, significantly enhancing inference performance and overall efficiency.
⚠️ Important Consideration: While exceptional for instruction-following, Falcon Instruct (40B) is not the optimal choice for further fine-tuning projects. For custom model development, it is recommended to start directly from the Falcon-40B base model. For a more resource-friendly alternative in instruction-based tasks, Falcon-7B-Instruct serves as an excellent option.
💡 Model Technical Highlights
- Architecture: Based on a causal decoder-only framework, primarily focusing on English and French languages, stemming from a fine-tuned Falcon-40B model.
- Strategic Training: Fine-tuned using a blend of 150 million tokens from the Baize dataset and 5% from RefinedWeb data, employing the Falcon-7B/40B tokenizer for optimal understanding.
- Specifications: Defined by 60 layers and a d_model of 8192, with an architecture incorporating innovative elements like rotary positional embeddings and parallel attention mechanisms for enhanced performance.
✅ Guidance for Users and Responsible Deployment
Given its advanced capabilities, Falcon Instruct (40B) is primarily recommended for direct chat-based interactions. For responsible application in production environments, users are strongly encouraged to implement safeguard measures and conduct thorough risk assessments.
⚠️ Language Bias Awareness: It's crucial to acknowledge the model's English-centric training. This may lead to inherent biases and stereotypes, potentially limiting its effectiveness and suitability for applications in other languages.
📚 License and Further Resources
Falcon Instruct (40B) is freely available under the Apache 2.0 license, fostering widespread use and development. Forthcoming papers and additional resources will provide deeper insights into its development and various applications. Whether you're developing sophisticated chatbots or seeking to enhance your application's language processing functions, Falcon Instruct (40B) offers a robust foundation for innovation and excellence in the field of AI language models.
💻 API Example
To integrate Falcon Instruct (40B) into your applications, you would typically use an API call structure similar to the following (actual implementation details may vary based on your environment and specific API provider):
{
"model": "tiiuae/falcon-40b-instruct",
"messages": [
{"role": "user", "content": "Explain Falcon Instruct (40B) in simple terms."}
],
"max_tokens": 150,
"temperature": 0.7
}
❓ Frequently Asked Questions (FAQs)
Q1: What is Falcon Instruct (40B) primarily designed for?
A1: Falcon Instruct (40B) is specifically optimized for chat-based interactions and following instructions, making it highly effective for conversational AI and command execution tasks.
Q2: Is Falcon Instruct (40B) suitable for further fine-tuning?
A2: While excellent as an instruct model, it is not recommended for further fine-tuning. For custom model development, starting with the foundational Falcon-40B base model is advised.
Q3: What are the main languages Falcon Instruct (40B) supports?
A3: The model primarily focuses on and performs best with English and French languages, reflecting its training data composition.
Q4: What is the licensing model for Falcon Instruct (40B)?
A4: Falcon Instruct (40B) is released under the Apache 2.0 license, which allows for broad use, distribution, modification, and patent use for both commercial and non-commercial purposes.
Q5: How does Falcon Instruct (40B) differentiate itself from other open-source models?
A5: It distinguishes itself through top performance on the OpenLLM Leaderboard, a highly optimized architecture featuring FlashAttention and multiquery attention, and its robust capability for instruction following, making it a leading choice in the open-source LLM space.
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