Tutorial
Tutorial: Scalable and Distributed ML Workflows with DVC and Ray on AWS (Part 2)
Need to setup DVC to work with Ray Cluster on AWS? This tutorial has you covered!
Tutorial: Scalable and Distributed ML Workflows with DVC and Ray (Part 1)
This tutorial introduces you to integrating DVC (Data Version Control) with Ray, turning them into your go-to toolkit for creating automated, scalable, and distributed ML pipelines.
Running DVC on a SLURM cluster
Learn how Exscientia uses DVC experiments on a cloud-deployed SLURM cluster to scale their ML experimentation.
Leveraging LLMs in Chatbots: The DVC Approach
Read how DVC can optimize the development process for chatbots built on Large Language Models.
Fine-Tuning Large Language Models with a Production-Grade Pipeline
This post describes a production ML pipeline for fine-tuning large language models using DVC, SkyPilot, HuggingFace Transformers, and quantization techniques.
Automate model deployment to Amazon SageMaker with the DVC Model Registry
DVC provides a Git-based mechanism to automate model deployment from an intuitive web UI.
Managing OpenFOAM Physical Simulations with DVC, CML, and Studio (Part 2)
In this second part, we discuss how to utilize cloud computing resources and visualize simulation data with CML and Iterative Studio.
Automate Your ML Pipeline: Combining Airflow, DVC, and CML for a Seamless Batch Scoring Experience
This tutorial shows you how to supercharge your batch scoring workflow by harnessing the power of Aiflow, DVC and CML.
MLEM + Modal + nanoGPT
Train and deploy your own GPT model in 2 easy steps!
