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Create a new pipeline

Launch and scale AI workloads without the hassle of managing infrastructure

Overview

Launch a barebone GPU-accelerated workload

Quickstart

Launch a Jupyter Notebook server with an SSH connection

GPU-accelerated notebook

Launch an interactive web app for Stable Diffusion

Stable Diffusion playground

Fine-tune Llama 3.1-8B with instruction datasets

Llama 3.1 fine-tuning

Serve & deploy vLLM-accelerated Llama 3.1-8B

Llama 3.1 deployment

Serve & deploy with Text Generation Inference (TGI)

Serverless deployment

Create a new run

Manage runs

Tracking runs

Create a new workspace

Explore workspaces

Create an SSH connection

Download & attach datasets

Run a server application

Create your own custom image in Workspace on VESSL AI

Build a custom image

Tips & Limitations

Create a new service

Manage API keys (Provisioned Mode)

Migrate from Service Beta

Run pipeline executions

Create & manage pipeline triggers

Create a new experiment

Manage experiments

Monitor experiment results

Run distributed training jobs

Create a new sweep

Monitor sweeps

VESSL Storage

External Storage

Monitor clusters

Create a new model

Deploy models

Create a new Organization

Create a new project

Auto-mount repository & Slack notification

See the full list of compute options and pricing

Pricing & Compute

Product updates

See VESSL Run in action with common use cases and workflows

Use cases

Use VESSL Service to create a Slack Summarizer Bot with Open-Source Llama 3

Create a Slack Summarizer Bot with VESSL Service

Leverge the power of GPUs to efficiently train batch runs

Launch batch jobs on GPUs

Enable a real-time session of interacitve run on GPUs.

Spin-up a notebook server on GPUs

Backup & Restore data with Artifacts

Use VESSL AI Python SDK to log and track runs

Track runs with vessl.log()

Import, export, and mount your data in your cloud object storage like AWS S3 or GCP GCS.

Use object storage with VESSL Run

VESSL Run is configured through a single YAML file.

Run YAML

VESSL Serve is configured through a single YAML file.

Serve YAML

Cheat Sheet

vessl cluster

vessl configure

vessl experiment

vessl image

vessl model

vessl organization

vessl project

vessl run

vessl service

vessl ssh-key

vessl storage

vessl sweep

vessl workspace

vessl dataset (Deprecated)

vessl volume (Deprecated)

Keras

Transformers

vessl.configure

vessl.log

vessl.Image

vessl.Audio

vessl.hp.update

vessl.progress

Cluster

Experiment

Image

Model

Organization

Project

RunnerBase

Service

SSH-key

Storage

Sweep

Workspace

Dataset (Deprecated)

Volume (Deprecated)

Send a request

Create an asynchronous request

Fetch output of an asynchronous request