Llama 3.1 8b
Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks.
API
If you're looking for an API, you can choose from your desired programming language.
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const axios = require('axios');
const api_key = "YOUR API-KEY";
const url = "https://api.segmind.com/v1/llama-v3p1-8b-instruct";
const data = {
"messages": [
{
"role": "user",
"content": "tell me a joke on cats"
},
{
"role": "assistant",
"content": "here is a joke about cats..."
},
{
"role": "user",
"content": "now a joke on dogs"
}
]
};
(async function() {
try {
const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } });
console.log(response.data);
} catch (error) {
console.error('Error:', error.response.data);
}
})();Attributes
An array of objects containing the role and content
Could be "user", "assistant" or "system".
A string containing the user's query or the assistant's response.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
llama 3.1 8B Instruct
The Llama 3.1-8B-Instruct is an advanced LLM, meticulously tuned for synthetic data generation, distillation, and inference. It is part of a remarkable collection of multilingual large language models (LLMs). These models are designed for various natural language understanding and generation tasks. Specifically, the 8-billion-parameter variant of Llama 3.1 is meticulously tuned for dialogue and instruction-based use cases.
Technical Details
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Model Name: 3.1-8B-Instruct
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Parameter Count: 8 billion parameters
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Architecture: Llama 3.1 uses an optimized transformer architecture. These transformers are the backbone of many state-of-the-art language models, allowing them to understand context and generate coherent text.
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Training Data: Trained on a diverse dataset comprising a wide array of text sources, ensuring comprehensive understanding and nuanced language generation.
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Performance Metrics: Demonstrated superior benchmarks across various NLP tasks, including text classification, sentiment analysis, machine translation, and more.
Key Features of 3.1 8B Instruct
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High Precision: Capable of understanding complex instructions and generating accurate responses, enhancing user experience across multiple applications.
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Flexibility: Ideal for a variety of tasks such as content creation, automated customer support, summarization, and more.
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Efficiency: Designed to process large volumes of data quickly, ensuring fast and reliable performance.
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Customizability: Easily fine-tuned to suit specific use cases, providing tailored solutions for unique industry needs.
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