Running Stable Diffusion Locally & in Cloud with Diffusers & dstack

This page summarizes the projects mentioned and recommended in the original post on dev.to

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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SaaSHub helps you find the best software and product alternatives
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  • diffusers

    🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

  • To help you overcome this challenge, we have written an article to guide you through the simple steps of using both diffusers and dstack to generate images from prompts, both locally and in the cloud, using a simple example.

  • dstack

    An open-source container orchestration engine for running AI workloads in any cloud or data center. https://discord.gg/u8SmfwPpMd

  • To help you overcome this challenge, we have written an article to guide you through the simple steps of using both diffusers and dstack to generate images from prompts, both locally and in the cloud, using a simple example.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • safetensors

    Simple, safe way to store and distribute tensors

  • Note: Using the safetensors library for storing tensors instead of pickle, as recommended by Hugging Face for better safety and speed.

  • dstack-examples

    A collection of examples demonstrating how to use dstack

  • The source code for this tutorial can be found on GitHub.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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