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Fast inference engine for Transformer models in C++.

Curated list of awesome vector search framework/engine, library, cloud service and research papers to vector similarity search.

Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.

MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.

Scalable deep learning training platform with integrated hyperparameter tuning support; includes Hyperband, PBT, and other search methods.

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

10x faster, cheaper, and better vector database.

Eurybia monitors data and model drift over time and securizes model deployment with data validation.

Interactive reports to analyze ML models during validation or production monitoring.

A library for efficient similarity search and clustering of dense vectors.

Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.

Feature store for machine learning.

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

FeatherCNN is a high performance inference engine for convolutional neural networks.

An enterprise-grade, high performance feature store.

A Virtual Feature Store. Turn your existing data infrastructure into a feature store.

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

Running large language models on a single GPU for throughput-oriented scenarios. (Archived).

Drag & drop UI to build your customized LLM flow using LangchainJS.

Library for high performance deep learning inference on NVIDIA GPUs.

Open-source self-hostable end-to-end LLMOps platform unifying tracing, evals, simulations, datasets, gateway, and guardrails.

Production-grade SDK for observability, automated evaluations and prompt management with sub-100ms guardrails for LLM/agent workflows.

Testing framework dedicated to ML models, from tabular to LLMs. Detect risks of biases, performance issues and errors in 4 lines of code.