Grok-1

Grok-1 is a 314-billion-parameter Mixture-of-Experts (MoE) large language model developed by xAI. Designed to optimize computational efficiency, it activates only 25% of its weights for each input token. In March 2024, xAI released Grok-1's model weights and architecture under the Apache 2.0 license, making them openly accessible to developers. The accompanying GitHub repository provides JAX example code for loading and running the model. Due to its substantial size, utilizing Grok-1 requires a machine with significant GPU memory. The repository's MoE layer implementation prioritizes correctness over efficiency, avoiding the need for custom kernels.

This is a full repo snapshot ZIP file of the Grok-1 code.

Features

314-billion-parameter Mixture-of-Experts (MoE) architecture
Efficient computation, activating only 25% of parameters per token
Fully open-source under the Apache 2.0 license
JAX-based implementation with example code provided
Scalable and modular, designed for research and development
Requires high GPU memory for inference and fine-tuning
Correctness-focused MoE layer without custom kernels
Optimized for natural language understanding and generation

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License

Apache License V2.0

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dappervoid Posted 2025-02-27

Really great model

Additional Project Details

Languages

English

Programming Language

Python

Related Categories

Python Large Language Models (LLM), Python AI Models

Registered

2025-02-27

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