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Interactive reports to analyze ML models during validation or production monitoring.
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A library for efficient similarity search and clustering of dense vectors.
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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FeatherCNN is a high performance inference engine for convolutional neural networks.
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An enterprise-grade, high performance feature store.
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A Virtual Feature Store. Turn your existing data infrastructure into a feature store.
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Open-source self-hostable end-to-end LLMOps platform unifying tracing, evals, simulations, datasets, gateway, and guardrails.
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Create customizable UI components around your models.
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Python materials for the online course on diffusion models by @huggingface.
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Kubernetes-based system for hyperparameter tuning and neural architecture search.
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Kubernetes custom resource definition for serving ML models on arbitrary frameworks.
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
github.com
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Standardized Serverless ML Inference Platform on Kubernetes.
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Open-source all-in-one platform for engineering AI products. Traces, Evals, Datasets, Labels.
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Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Neural network inference from the command line, implemented in CHICKEN Scheme.
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A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.
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UI tool for fine-tuning and testing your own LoRA models base on LLaMA, GPT-J and more. One-click run on Google Colab. + A Gradio ChatGPT-like Chat UI to demonstrate your language models.
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Version and deploy your ML models following GitOps principles.
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Open source MLOps platform that helps you collaborate, reproduce and share your ML work.