Snowflake Arctic Instruct

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Snowflake Arctic Instruct

Snowflake Arctic Instruct: Open-source enterprise LLM with 480B parameters, excelling in SQL, coding, and instruction following tasks. Apache-2.0 licensed.

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Snowflake Arctic Instruct

Efficient enterprise-grade LLM with dense-MoE architecture for diverse AI applications.

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

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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.

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