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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: 'NousResearch/Nous-Hermes-Llama2-70b',
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="NousResearch/Nous-Hermes-Llama2-70b",
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
Discover Nous Hermes LLaMA-2 (70B): A Powerful LLM
The Nous-Hermes-Llama2-70b represents a significant advancement in large language models (LLMs), meticulously developed by Nous Research. Launched in May 2023, this formidable model boasts 70 billion parameters and is engineered using the advanced LLaMA and Llama-2 architectures. Its primary objective is to deliver robust performance across an extensive array of natural language processing (NLP) tasks.
✅ Model Name: Nous-Hermes Llama2
✨ Developer/Creator: Nous Research
🗓️ Release Date: May 2023
🧠 Version: 70B
💡 Model Type: Large language model (LLM)
Key Features and Distinct Advantages
Nous-Hermes-Llama2-70b distinguishes itself with a suite of impressive capabilities designed for reliability and versatility:
- 📝 Exceptional Long-form Responses: Capable of generating detailed and coherent narratives with extended length.
- 🚫 Minimized Hallucination Rate: Engineered to provide highly factual and accurate outputs, reducing the incidence of generated misinformation.
- 📚 Comprehensive Training Data: Benefited from training on synthetic GPT-4 outputs and specialized datasets such as GPTeacher, roleplay, code instruct, Nous Instruct, and PDACTL.
- 🎯 Enhanced Subject-Specific Knowledge: Further refined by incorporating domain-specific datasets from Camel-AI and Airoboros, broadening its expertise.
Intended Use Cases and Applications
The Nous-Hermes-Llama2-70b model is a versatile tool designed for a wide spectrum of general-purpose language tasks. Its reliable performance and low hallucination rate make it particularly valuable for:
- ▶ Instruction Following: Executing complex and nuanced instructions with high accuracy.
- ▶ Task Automation: Streamlining and automating various language-centric workflows.
- ▶ Data Analysis: Facilitating insightful extraction and interpretation of textual data.
- ▶ Text Generation: Producing high-quality content for diverse needs, from creative writing to technical documentation.
- ▶ Fact-Checking & Research: Its low hallucination rate makes it suitable for applications requiring high factual integrity.
🌐 Multilingual Support: In addition to English, the model extends its capabilities to German, Spanish, French, and other languages, enhancing its global utility.
Technical Details and Specifications
🛠️ Model Architecture
Nous-Hermes-Llama2-70b is built upon the robust AutoModelForCausalLM architecture from the Hugging Face transformers library. It faithfully implements the foundational LLaMA and Llama-2 model architectures, which are intrinsically based on the standard Transformer decoder.
📊 Training Data Overview
The model's extensive knowledge and linguistic prowess are a direct result of its training on a highly diverse and rich dataset, which includes:
- Synthetic outputs generated by GPT-4
- Specialized datasets such as GPTeacher, roleplay, code instruct, Nous Instruct, and PDACTL
- Subject-specific knowledge from Camel-AI and Airoboros datasets
This comprehensive training regimen ensures broad knowledge and sophisticated language understanding.
📦 Data Source and Scale
While the precise scale and constituent elements of the training data are not publicly detailed, the model's significant 70 billion parameters unequivocally suggest a tremendously large underlying dataset.
📅 Knowledge Cutoff Date
The exact knowledge cutoff date for Nous-Hermes-Llama2-70b has not been officially disclosed. However, given its release timeframe in May 2023, it is reasonable to assume its knowledge base extends up to early 2023.
Performance, Comparison & Ethical Guidelines
🚀 User Feedback and Performance Metrics
Nous-Hermes-Llama2-70b has garnered widespread positive feedback from its user base, who frequently commend its high coherence and notably low hallucination rate. While specific, publicly reported performance benchmarks are currently unavailable, anecdotal evidence strongly supports its capabilities.
⚖️ Diversity and Bias Considerations
Nous Research has not publicly released detailed information concerning the diversity of the training data utilized or any identified potential biases within the model. Nevertheless, the intentional inclusion of datasets from sources such as Camel-AI and Airoboros, known for their focus on varied topics and perspectives, suggests a conscious effort toward mitigating inherent biases.
🆚 Comparison with Peer Models
Direct, published comparative benchmarks pitting Nous-Hermes-Llama2-70b against other leading large language models are not yet readily available. However, its substantial 70 billion parameters firmly places it within the elite category of models, comparable in scale to industry giants like GPT-3 and PaLM.
📜 Ethical Guidelines and Licensing
While Nous Research has not published specific ethical guidelines for the use of Nous-Hermes-Llama2-70b, the company consistently advocates for responsible AI development and underscores the critical importance of transparency and accountability in all its AI initiatives.
The model is distributed under the MIT license, which permits both commercial and non-commercial deployment, provided that appropriate attribution is given.
Engaging with Nous Hermes LLaMA-2 (70B)
For developers and researchers, integrating Nous-Hermes-Llama2-70b into various applications and workflows is typically facilitated through standard API access points. Detailed documentation, comprehensive usage guides, and platform-specific examples are generally provided by Nous Research or accessible via prominent AI platforms like Hugging Face. This ensures a straightforward adoption process for a diverse range of NLP and AI-driven initiatives.
(Specific API usage examples and code snippets are best referenced in the model's official documentation or within the respective platform interfaces.)
❓ Frequently Asked Questions (FAQ)
Q1: What is Nous-Hermes-Llama2-70b?
A1: It is a 70 billion parameter large language model (LLM) developed by Nous Research, released in May 2023, recognized for its strong performance in NLP tasks and a low hallucination rate.
Q2: What are the primary applications of this model?
A2: It's well-suited for a variety of general-purpose language tasks, including instruction following, task automation, data analysis, and sophisticated text generation, particularly in scenarios demanding high factual accuracy.
Q3: Which languages does Nous-Hermes-Llama2-70b support?
A3: The model offers robust support for English, German, Spanish, and French, alongside compatibility with other languages.
Q4: Under what license is the model released?
A4: It is released under the MIT license, which permits broad commercial and non-commercial use, provided proper attribution is maintained.
Q5: What is the approximate knowledge cutoff date for the model?
A5: While not precisely specified, given its release in May 2023, the model's knowledge base is estimated to be current up to early 2023.
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