Serve, optimize and scale PyTorch models in production
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Updated
Aug 6, 2025 - Java
Serve, optimize and scale PyTorch models in production
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.
A universal scalable machine learning model deployment solution
A stand alone industrial serving system for angel.
This code is used to build & run a Docker container for performing predictions against a Spark ML Pipeline.
Enterprise-grade LLMOps platform to accelerate the development and deployment of generative AI applications.
Exposes a serialized machine learning model through a HTTP API.
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.
Fork of pytorch/serve. Serve, optimize and scale PyTorch models in production
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