Basic Information
Model Name: Snowflake Arctic Instruct
Developer/Creator: Snowflake AI Research Team
Release Date: April 24, 2024
Version: Not specified
Model Type: Large Language Model (LLM)
Description
Overview
Snowflake Arctic Instruct is an efficient, intelligent, and open-source language model developed by the Snowflake AI Research Team. It combines a dense transformer model with a Mixture of Experts (MoE) architecture, resulting in a powerful and flexible foundation for building AI-powered applications.
Key Features
- Dense-MoE Hybrid transformer architecture
- 480 billion total parameters, 17 billion active parameters
- Optimized for inference efficiency
- Instruction-tuned for improved performance on enterprise tasks
- Apache-2.0 license for free use in research, prototypes, and products
Intended Use
Snowflake Arctic Instruct is designed for enterprise-level AI applications, excelling at tasks such as:
- SQL generation
- Code generation and understanding
- Complex instruction following
- Dialogue and conversational AI
- Summarization
- General language understanding and generation
Language Support
The model supports text input and output, including code generation.
Technical Details
Architecture
Snowflake Arctic Instruct features a unique Dense-MoE Hybrid transformer architecture:
- 10 billion parameter dense transformer model
- Residual 128x3.66 billion parameter MoE Multilayer Perceptron (MLP)
- Top-2 gating technique for selecting active parameters
- 35 transformer layers
Training Data
The training process for Arctic was split into three distinct stages, totaling approximately 3.5 trillion tokens:
- Phase 1: 1 trillion tokens
- Phase 2: 1.5 trillion tokens
- Phase 3: 1 trillion tokens
This multi-stage approach allowed different competencies to be wired logically, optimizing the model's performance on enterprise-focused tasks.
Knowledge Cutoff
The knowledge cutoff date is up to early 2024.
Performance Metrics
Snowflake Arctic Instruct demonstrates strong performance across various benchmarks:
- Excels at enterprise-specific tasks
- Outperforms DBRX, Mixtral 8x7B, and Llama 2 70B on average across enterprise benchmarks
- Competitive performance on general commonsense reasoning benchmarks
- Achieves a score of 7.95 on MTBench, with a turn-1 score of 8.31
- Performs competitively on the Helpful, Honest, & Harmless (HHH) alignment dataset
Usage
Code Samples
const { OpenAI } = require('openai');
const api = new OpenAI({
baseURL: 'https://api.aimlapi.com/v1',
apiKey: '<YOUR_API_KEY>',
});
const main = async () => {
const result = await api.chat.completions.create({
model: 'Snowflake/snowflake-arctic-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();
Ethical Guidelines
While specific ethical guidelines are not mentioned in the search results, the model is released under an Apache-2.0 license, allowing free use in research, prototypes, and products.
Licensing
License Type: Apache-2.0The Apache-2.0 license allows users to freely use, modify, and distribute the model in both commercial and non-commercial applications.