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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
License
Apache License V2.0Follow Grok-1
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Really great model