This New API Makes It Easy And Cheap For Developers To Build Machine Learning ML-Powered Apps Using Stable Diffusion

It is simple for developers to create Machine Learning ML-powered applications using TuneMyAI. Stable Diffusion models can be adjusted and deployed by developers with only a few lines of code, with no setup hassles. An app developer spent some time attempting to find out how to set up their infrastructure using Kubernetes to move beyond local GPUs and laptops. Developers may adjust their Stable Diffusion models for certain data sets using the API. It manages everything, including model deployment, inference, and fine-tuning, and integrates with HuggingFace. The group is developing several fresh features, such as hosted WebUIs and support for extra models like Whisper.

How does it work?

1. Upload Images: Upload subject-related photos using an API call with a special token for the subject and a class that describes the subject.
2. Finetune: Choose the base model that wants to base the picture adjustments. It works with HuggingFace to integrate so that one may utilize any repository.
3. Inference: Use the prompts and options of choice when creating the endpoint. It also provides face repair and scaling up.

The process for fine-tuning a model is a two-step process:

1. Define and upload dataset(s)
2. Create a training job with the dataset(s) to fine-tune on

Key Features

• Very Fast
• Hugging Face Integration
• Multiple Classes
• Customizable
• Simple and transparent pricing
• Provides dedicated model hosting

Goal

The construction of ML-powered industrial apps is complex. During the development of Picasso AI, where TuneMyAI created our infrastructure to manage scaling up of fine-tuning and inference, they had firsthand experience with this. As a result, they are on a quest to make developing ML models relatively accessible by letting developers create ML-enabled applications on top of them using an exceedingly straightforward API.

To get started, check this link: https://tunemy.ai/

To learn more, check out their API Docs here.

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