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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/Meta-Llama-3-8B-Instruct-Lite',
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/Meta-Llama-3-8B-Instruct-Lite",
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 Llama 3 8B Instruct Lite
The Llama 3 8B Instruct Lite model, developed by Meta and released on April 18, 2024, is a powerful text generation model optimized for interactive dialogue and precise instruction-following.
✨ Key Highlights:
- ✓ Optimized Architecture: Utilizes Grouped-Query Attention for enhanced scalability.
- ✓ Instruction-Tuned: Benefits from Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) for superior alignment.
- ✓ High Performance: Consistently outperforms many leading open-source chat models across industry benchmarks.
- ✓ Safety & Helpfulness: Engineered to provide helpful and safe responses, adhering to responsible AI principles.
🎯 Intended Use & Language Support
This model is primarily designed for commercial and research applications, particularly in the development of sophisticated assistant-like chatbots and various other natural language generation tasks.
While its primary language support is English, there is potential for fine-tuning in other languages, subject to specific licensing agreements.
⚙️ Technical Specifications
Architecture:
Llama 3 is an auto-regressive language model built upon a robust transformer architecture. It incorporates Grouped-Query Attention (GQA) to significantly enhance inference scalability. Instruction-tuned versions are further refined using SFT and RLHF to align outputs with human preferences.
Training Data:
- Source: Compiled from publicly available online datasets.
- Scale: Trained on an extensive dataset of over 15 trillion tokens.
- Knowledge Cutoff: The 8B model's knowledge extends up to March 2023.
- Diversity & Bias: Extensive efforts are made to ensure diverse training data, with ongoing evaluations to minimize potential biases.
📊 Performance Benchmarks
Accuracy Metrics:
-
68.4
MMLU (5-shot) -
72.6
CommonSenseQA (7-shot) -
62.2
HumanEval (0-shot)
Speed & Robustness:
The model is meticulously optimized for real-time applications, boasting highly efficient inference capabilities.
It demonstrates exceptional generalization across diverse topics and languages, effectively processing a wide range of inputs with strong robustness.
📖 Usage & Ethical Guidelines
Responsible Deployment:
Meta provides a comprehensive Responsible Use Guide, outlining best practices for ethical model deployment. Developers are strongly advised to integrate advanced safety measures, including Meta Llama Guard 2 and Code Shield safeguards.
Licensing:
Specific details regarding the custom commercial license can be found by clicking here (Meta Llama 3 License).
⚡ Hardware & Carbon Footprint
Training involved Meta's advanced Research SuperCluster complemented by third-party cloud compute resources for fine-tuning and evaluation.
Carbon Footprint Summary:
- Llama 3 8B: 1.3M GPU hours, 700W, 390 tCO2eq
- Total (across all Llama 3 models): 7.7M GPU hours, 2290 tCO2eq (100% offset by Meta’s sustainability program)
🛡️ Responsibility & Safety
Meta maintains an unwavering commitment to responsible AI development, advocating an open approach. The Llama 3 release is accompanied by updated guidelines and resources to empower developers in implementing effective model safety.
Key Safety Measures Implemented:
- ✓ Extensive Red Teaming: Rigorous adversarial evaluations to identify and mitigate vulnerabilities.
- ✓ Refusals Mitigation: Strategies to minimize false refusals and improve user experience.
- ✓ Responsible Release Processes: Designed to address potential misuse and critical risks proactively.
❓ Frequently Asked Questions (FAQ)
What is Llama 3 8B Instruct Lite?
Llama 3 8B Instruct Lite is an advanced generative text model from Meta, released on April 18, 2024. It is specifically optimized for dialogue and following instructions accurately, leveraging a refined transformer architecture with Grouped-Query Attention.
What are the primary applications for this model?
It is intended for both commercial and research purposes, excelling in creating assistant-like chatbots and various other natural language generation tasks where precise instruction-following and natural dialogue are crucial.
What training data was used for Llama 3 8B?
The model was trained on over 15 trillion tokens from publicly available online data, with its knowledge cutoff for the 8B version set at March 2023. Meta emphasizes diversity and ongoing bias evaluation in its datasets.
How does Meta ensure the safety of Llama 3 models?
Meta employs extensive safety measures, including red teaming, adversarial evaluations, refusals mitigation to prevent false refusals, and responsible release processes. They also provide a Responsible Use Guide and advocate for using safeguards like Meta Llama Guard 2 and Code Shield.
Where can I find the licensing details for Llama 3?
Details for the custom commercial license are available on Meta's official Llama website. You can find the specific terms by following the provided link: Meta Llama 3 License.
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