Enterprise Plans
AI Application Development
AI Translator API
AI SEO/GEO Service
Web Scraping Service
Log in
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: 'mistralai/mistral-nemo',
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="mistralai/mistral-nemo",
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}")
-
AI Playground
Test all API models in the sandbox environment before you integrate.
We provide more than 300 models to integrate into your app.
Product Detail
Introducing Mistral-Nemo: A Powerful LLM for Advanced NLP
Discover Mistral-Nemo, a cutting-edge large language model (LLM) co-developed by Mistral AI and NVIDIA, released on July 18, 2024. This state-of-the-art model (Version 0.1) is engineered for a wide array of advanced natural language processing tasks, including sophisticated text generation, precise summarization, accurate translation, and insightful sentiment analysis. Its remarkable 128k token context window sets it apart, enabling the handling of extensive inputs and complex, multi-faceted tasks with unparalleled efficiency.
🛈 Key Highlights:
- ✓ Robust Performance: Equipped with 12 billion parameters.
- ✓ Expansive Context Window: Supports up to 128k tokens, ideal for lengthy content.
- ✓ Instruction-Tuned: Optimized for superior task performance and prompt adherence.
- ✓ Multilingual Mastery: Capable across over 10 languages, including English, French, Spanish, and Chinese.
- ✓ Efficient Tokenization: Leverages the Tekken tokenizer for effective text and code compression.
Intended Applications & Global Reach
Mistral-Nemo is meticulously crafted for applications demanding high-quality text generation. This includes innovative chatbots, efficient content creation tools, accurate document summarization, and comprehensive multilingual communication solutions. Its broad language support ensures versatility for global deployments and diverse user bases.
Technical Architecture & Training Insight
💻 Architecture Details:
Built upon a robust Transformer architecture, Mistral-Nemo features key specifications:
- Layers: 40
- Hidden Dimension: 14,436
- Head Dimension: 128
- Number of Heads: 32
- Activation Function: SwiGLU
Advanced techniques such as Grouped Query Attention and Sliding Window Attention are integrated to further enhance its performance capabilities.
📚 Comprehensive Training Data:
The model underwent training on an extensive and diverse dataset, encompassing billions of tokens from multilingual text and code. This broad training ensures a deep understanding of language nuances across various domains.
- Data Sources: Includes literature, web pages, and programming documentation.
- Knowledge Cutoff: Current as of April 2024.
- Bias Mitigation: Mistral AI actively implemented strategies to reduce bias by ensuring a dataset that represents multiple cultures and languages, enhancing the model's robustness and fairness.
Exceptional Performance Benchmarks
Mistral-Nemo has consistently demonstrated strong performance across various critical benchmarks:
- ★ High Accuracy: Achieves impressive accuracy on tasks like HellaSwag and Winogrande.
- ★ Category Leader: Outperforms comparable models in its size category, particularly in reasoning and coding accuracy.
Mistral-Nemo vs. Leading LLMs: A Performance Snapshot
Mistral-Nemo exhibits superior performance across a spectrum of tasks when compared to models such as Gemma 2 9B and Llama 3 8B. Its substantially larger 128k context window is a significant advantage, contributing to its leading scores in several key areas.
🚀 Mistral-Nemo (128k context)
- HellaSwag (0-shot): 83.5%
- Winogrande (0-shot): 76.8%
- TriviaQA (5-shot): 73.8%
- OpenBookQA (0-shot): 60.6%
- CommonSense QA (0-shot): 70.4%
📈 Gemma 2 9B (8k context)
- HellaSwag (0-shot): 80.1%
- TriviaQA (5-shot): 71.3%
- (Other benchmarks lower or not specified)
📈 Llama 3 8B (8k context)
- HellaSwag (0-shot): 80.6%
- TriviaQA (5-shot): 61.0%
- (Other benchmarks lower or not specified)
Comparative benchmark results highlighting Mistral-Nemo's leading performance.
How to Access & Utilize Mistral-Nemo
🔗 Code Samples & API Access:
Mistral-Nemo is readily available on the AI/ML API platform under the identifier "mistralai/mistral-nemo".
For detailed implementation, comprehensive API Documentation is available to guide developers through integration and usage.
import openai
client = openai.OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.ai.cc/v1",
)
chat_completion = client.chat.completions.create(
model="mistralai/mistral-nemo",
messages=[
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "Explain the benefits of Mistral-Nemo in a concise way."}
],
max_tokens=500,
temperature=0.7,
);
print(chat_completion.choices[0].message.content)Ethical Framework & Open Licensing
👤 Responsible AI Development:
Mistral AI is deeply committed to ethical considerations in AI development. The organization champions transparency regarding model capabilities and advocates for responsible usage to mitigate misuse and unintended consequences.
📜 Licensing & Accessibility:
Mistral-Nemo is released under the permissive Apache 2.0 license. This open licensing model promotes broad innovation and accessibility within the developer community by permitting both commercial and non-commercial usage rights.
Ready to integrate? Get the Mistral-Nemo API here!
Frequently Asked Questions (FAQ)
Q1: What is Mistral-Nemo and what are its primary uses?
A: Mistral-Nemo is an advanced large language model (LLM) developed by Mistral AI and NVIDIA. It's designed for natural language processing tasks such as text generation, summarization, translation, and sentiment analysis. Its primary uses include chatbots, content creation, document summarization, and multilingual communication.
Q2: What is the maximum context window supported by Mistral-Nemo?
A: Mistral-Nemo supports an impressive context window of up to 128,000 tokens, allowing it to process and understand very long inputs and complex conversations or documents.
Q3: How does Mistral-Nemo compare to other popular LLMs like Gemma 2 9B or Llama 3 8B?
A: Mistral-Nemo generally outperforms models of similar size, such as Gemma 2 9B and Llama 3 8B, particularly due to its significantly larger 128k context window and strong performance on reasoning and coding accuracy benchmarks like HellaSwag and Winogrande.
Q4: Is Mistral-Nemo available for commercial use?
A: Yes, Mistral-Nemo is released under the Apache 2.0 license, which permits both commercial and non-commercial usage, fostering broad adoption and innovation.
Q5: How can developers access Mistral-Nemo?
A: Developers can access Mistral-Nemo via the AI/ML API platform using the identifier "mistralai/mistral-nemo". Detailed API documentation is also available for integration guidance.
Learn how you can transformyour company with AICC APIs
