Cerebras Wafer-Scale cluster (R2.0.3)
Original Cerebras Installation Documentation (R1.6.1)
Cerebras AI Model Studio Documentation

Introduction

Overview
Weight Streaming Execution

Get Started

Run your first Cerebras job
Cerebras job scheduling and monitoring
Beginner Tutorials
- Training and fine-tuning a Large Language Model (LLM)
- Training a UNet for large image segmentation

Prepare your data

Data Processing and Dataloaders

Cerebras PyTorch API

Cerebras PyTorch API
Writing a Custom Training Loop

Cerebras Model Zoo

Model configuration using Cerebras Model Zoo
Cerebras Model Zoo YAML parameters
Convert checkpoints and model configs
- Work with Cerebras checkpoints
- Upgrade checkpoints from previous releases
Port model using Cerebras Model Zoo
- Port PyTorch model to Cerebras
Cerebras Model Zoo Supported Operations API
- modelzoo

Cerebras Guides

How-to Guides

Fundamentals

Model Development
For training and evaluating any model
Boosting Model performance

Support

Troubleshooting
Software Release Notes
Documentation Updates
User Authentication on a Cerebras Wafer-Scale cluster
Glossary

Model Development#

Kernel autogeneration with AutoGen
Define environment variables for input workers
Import user-specific dependencies in Cerebras environment
- How to Disable Custom Worker Container Workflow
Special considerations for CV dataloaders
- Adding support for using worker_cache with a new dataloader
- Example

previous

Run Cerebras Model Zoo on a GPU

next

Kernel autogeneration with AutoGen

© Copyright 2023, Cerebras Systems.

Created using Sphinx 4.4.0.