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?
The process for fine-tuning a model is a two-step process:
Key Features
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:
To learn more, check out their API Docs here.
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Dhanshree Shenwai is a Consulting Content Writer at MarktechPost. She is a Computer Science Engineer and working as a Delivery Manager in leading global bank. She has a good experience in FinTech companies covering Financial, Cards & Payments and Banking domain with keen interest in applications of AI. She is enthusiastic about exploring new technologies and advancements in today’s evolving world.

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