Explore Cerebras’ Documentation#
Cerebras's Wafer-Scale cluster offers a framework to train and evaluate a neural network with near-perfect linear scaling across millions of cores without the inconvenience of distributed computing. Bring your own ML model and dataset, or take advantage of our pre-configured Large Language Models(LLM) and Computer Vision(CV) models residing in Cerebras's Model Zoo.
Browse through this portal to gain access to Cerebras's core concepts, features, and Model Zoo. It also includes guides showing how to set up the Cerebras environment and Model Zoo. It also contains various how-to guides and tutorials that teach every aspect in detail. Begin by choosing your desired workflow.
Learn about Cerebras's framework that supports large-scale models up to and well beyond 1 billion parameters and large-scale inputs such as sequences of 50,000+ and 7k x 7k images. It can contain single or multiple CS-2 systems that can distribute jobs across all or a subset of CS-2 systems in the cluster. A supporting CPU cluster in this installation consists of MemoryX, SwarmX, management, and input worker nodes.
Learn about Cerebras's framework, designed as a single CS-2 node that supports models below 1 billion parameters with pipelined execution. It comprises a CS-2 system and a CPU cluster with CPU nodes acting as coordinators and input workers.
Learn about Cerebras's AI Model Studio, a computing service powered by Cerebras Wafer-Scale Clusters comprising 4+ CS-2s and hosted by Cirrascale Cloud Services. It is a purpose-built platform optimized for training and fine-tuning large language models on dedicated clusters of millions of cores.
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- Cerebras company website