3 boosters for "mlops" — AI-graded, open source, ready to install
A skill for adapting and optimizing Hugging Face or custom LLM models to run efficiently on vLLM with Ascend NPU support, enabling developers to validate and deploy models with deterministic testing and single-commit delivery.
An ML engineer agent that handles end-to-end production ML workflows including model serving, feature engineering, A/B testing, and monitoring for TensorFlow/PyTorch deployments. Ideal for teams building scalable ML systems who need guidance on MLOps best practices and production readiness.
A versatile AI agent that provides expert guidance across data engineering, machine learning, MLOps, and generative AI workflows—ideal for developers building production ML systems, data pipelines, and AI applications.
