promsoft / dstack

dstack is an open-source toolkit for running GPU workloads on any cloud. It works seamlessly with any cloud GPU providers. Discord: https://discord.gg/u8SmfwPpMd

Orchestrate GPU workloads effortlessly on any cloud

Docs • Examples • Discord

dstack is an open-source toolkit and orchestration engine for running GPU workloads. It's designed for development, training, and deployment of gen AI models on any cloud.

Supported providers: AWS, GCP, Azure, Lambda, TensorDock, Vast.ai, and DataCrunch.

Latest news ✨

• [2024/01] dstack 0.14.0: OpenAI-compatible endpoints preview (Release)
• [2023/12] dstack 0.13.0: Disk size, CUDA 12.1, Mixtral, and more (Release)
• [2023/11] dstack 0.12.3: Vast.ai integration (Release)
• [2023/10] dstack 0.12.2: TensorDock integration (Release)
• [2023/09] RAG with Llama Index and Weaviate (Example)
• [2023/08] Fine-tuning with QLoRA (Example)

Installation

Before using dstack through CLI or API, set up a dstack server.

Install the server

The easiest way to install the server, is via pip:

pip install "dstack[all]" -U

Configure credentials

If you have default AWS, GCP, or Azure credentials on your machine, the dstack server will pick them up automatically.

Otherwise, you need to manually specify the cloud credentials in ~/.dstack/server/config.yml.

For further details on setting up the server, refer to installation.

Start the server

To start the server, use the dstack server command:

$ dstack server

Applying configuration from ~/.dstack/server/config.yml...

The server is running at http://127.0.0.1:3000/
The admin token is "bbae0f28-d3dd-4820-bf61-8f4bb40815da"

Note It's also possible to run the server via Docker.

CLI & API

Once the server is up, you can use either dstack's CLI or API to run workloads. Below is a live demo of how it works with the CLI.

Dev environments

Dev environments allow you to quickly provision a machine with a pre-configured environment, resources, IDE, code, etc.

Tasks

Tasks make it very easy to run any scripts, be it for training, data processing, or web apps. They allow you to pre-configure the environment, resources, code, etc.

Services

Services make it easy to deploy models and apps cost-effectively as public endpoints, allowing you to use any frameworks.

More information

For additional information and examples, see the following links:

• Docs
• Examples
• Discord

Licence

Mozilla Public License 2.0